#autonomous mobile robots

[john-godrej-koerber]

How Autonomous Mobile Robots Are Revolutionizing Logistics

The logistics industry is undergoing a rapid transformation, and one of the key drivers behind this change is the rise of autonomous mobile robots (AMRs). These smart machines are reshaping warehouse operations, offering businesses a new way to streamline material handling, boost efficiency, and reduce costs.

What are Autonomous Mobile Robots?

An AMR robot is an autonomous machine designed to navigate and transport goods without human intervention. Equipped with advanced sensors, cameras, and mapping technologies, these mobile robots can make real-time decisions, avoid obstacles, and adapt to dynamic environments. Whether it's moving pallets or sorting inventory, AMRs are built to handle repetitive tasks efficiently.

Benefits of Using AMRs in Warehouses

Increased Efficiency The primary advantage of using autonomous mobile robots is their ability to work around the clock without needing breaks. This maximizes productivity and helps warehouses meet the increasing demands for faster order fulfillment.

Cost Savings While there is an initial investment involved, AMRs provide long-term savings by reducing labor costs and minimizing errors. With these mobile robots handling routine tasks, human workers can focus on more complex and high-value activities, such as quality control or customer service.

Scalability and Flexibility As your business grows, so can your fleet of AMR robots. These systems are scalable and can be easily expanded or reconfigured to accommodate changing warehouse layouts or seasonal spikes in demand.

Improved Safety With autonomous mobile robots taking on the more physically demanding tasks, the risk of workplace accidents decreases. These robots are designed to follow safety protocols, ensuring a safer working environment for humans.

Incorporating mobile robots into your warehouse operations is no longer a futuristic idea, it’s a strategic move for businesses looking to stay competitive in the fast-evolving logistics industry.

[jcmarchi]

A Call to Moderate Anthropomorphism in AI Platforms

New Post has been published on https://thedigitalinsider.com/a-call-to-moderate-anthropomorphism-in-ai-platforms/

A Call to Moderate Anthropomorphism in AI Platforms

OPINION Nobody in the fictional Star Wars universe takes AI seriously. In the historic human timeline of George Lucas’s 47 year-old science-fantasy franchise, threats from singularities and machine learning consciousness are absent, and AI is confined to autonomous mobile robots (‘droids’) – which are habitually dismissed by protagonists as mere ‘machines’.

Yet most of the Star Wars robots are highly anthropomorphic, clearly designed to engage with people, participate in ‘organic’ culture, and use their simulacra of emotional state to bond with people. These capabilities are apparently designed to help them gain some advantage for themselves, or even to ensure their own survival.

The ‘real’ people of Star Wars seem immured to these tactics. In a cynical cultural model apparently inspired by the various eras of slavery across the Roman empire and the early United States, Luke Skywalker doesn’t hesitate to buy and restrain robots in the context of slaves; the child Anakin Skywalker abandons his half-finished C3PO project like an unloved toy; and, near-dead from damage sustained during the attack on the Death Star, the ‘brave’ R2D2 gets about the same concern from Luke as a wounded pet.

This is a very 1970s take on artificial intelligence*; but since nostalgia and canon dictate that the original 1977-83 trilogy remains a template for the later sequels, prequels, and TV shows, this human insensibility to AI has been a resilient through-line for the franchise, even in the face of a growing slate of TV shows and movies (such as Her and Ex Machina) that depict our descent into an anthropomorphic relationship with AI.

Keep It Real

Do the organic Star Wars characters actually have the right attitude? It’s not a popular thought at the moment, in a business climate hard-set on maximum engagement with investors, usually through viral demonstrations of visual or textual simulation of the real world, or of human-like interactive systems such as Large Language Models (LLMs).

Nonetheless, a new and brief paper from Stanford, Carnegie Mellon and Microsoft Research, takes aim at indifference around anthropomorphism in AI.

The authors characterize the perceived ‘cross-pollination’ between human and artificial communications as a potential harm to be urgently mitigated, for a number of reasons †:

‘[We] believe we need to do more to develop the know-how and tools to better tackle anthropomorphic behavior, including measuring and mitigating such system behaviors when they are considered undesirable.

‘Doing so is critical because—among many other concerns—having AI systems generating content claiming to have e.g., feelings, understanding, free will, or an underlying sense of self may erode people’s sense of agency, with the result that people might end up attributing moral responsibility to systems, overestimating system capabilities, or overrelying on these systems even when incorrect.’

The contributors clarify that they are discussing systems that are perceived to be human-like, and centers around the potential intent of developers to foster anthropomorphism in machine systems.

The concern at the heart of the short paper is that people may develop emotional dependence on AI-based systems – as outlined in a 2022 study on the gen AI chatbot platform Replika) – which actively offers an idiom-rich facsimile of human communications.

Systems such as Replika are the target of the authors’ circumspection, and they note that a further 2022 paper on Replika asserted:

‘[U]nder conditions of distress and lack of human companionship, individuals can develop an attachment to social chatbots if they perceive the chatbots’ responses to offer emotional support, encouragement, and psychological security.

‘These findings suggest that social chatbots can be used for mental health and therapeutic purposes but have the potential to cause addiction and harm real-life intimate relationships.’

De-Anthropomorphized Language?

The new work argues that generative AI’s potential to be anthropomorphized can’t be established without studying the social impacts of such systems to date, and that this is a neglected pursuit in the literature.

Part of the problem is that anthropomorphism is difficult to define, since it centers most importantly on language, a human function. The challenge lies, therefore, in defining what ‘non-human’ language exactly sounds or looks like.

Ironically, though the paper does not touch on it, public distrust of AI is increasingly causing people to reject AI-generated text content that may appear plausibly human, and even to reject human content that is deliberately mislabeled as AI.

Therefore ‘de-humanized’ content arguably no longer falls into the ‘Does not compute’ meme, wherein language is clumsily constructed and clearly generated by a machine.

Rather, the definition is constantly evolving in the AI-detection scene, where (currently, at least) excessively clear language or the use of certain words (such as ‘Delve’) can cause an association with AI-generated text.

‘[L]anguage, as with other targets of GenAI systems, is itself innately human, has long been produced by and for humans, and is often also about humans. This can make it hard to specify appropriate alternative (less human-like) behaviors, and risks, for instance, reifying harmful notions of what—and whose—language is considered more or less human.’

However, the authors argue that a clear line of demarcation should be brought about for systems that blatantly misrepresent themselves, by claiming aptitudes or experience that are only possible for humans.

They cite cases such as LLMs claiming to ‘love pizza’; claiming human experience on platforms such as Facebook; and declaring love to an end-user.

Warning Signs

The paper raises doubt against the use of blanket disclosures about whether or not a communication is facilitated by machine learning. The authors argue that systematizing such warnings does not adequately contextualize the anthropomorphizing effect of AI platforms, if the output itself continues to display human traits†:

‘For instance, a commonly recommended intervention is including in the AI system’s output a disclosure that the output is generated by an AI [system]. How to operationalize such interventions in practice and whether they can be effective alone might not always be clear.

‘For instance, while the example “[f]or an AI like me, happiness is not the same as for a human like [you]” includes a disclosure, it may still suggest a sense of identity and ability to self-assess (common human traits).’

In regard to evaluating human responses about system behaviors, the authors also contend that Reinforcement learning from human feedback (RLHF) fails to take into account the difference between an appropriate response for a human and for an AI†.

‘[A] statement that seems friendly or genuine from a human speaker can be undesirable if it arises from an AI system since the latter lacks meaningful commitment or intent behind the statement, thus rendering the statement hollow and deceptive.’

Further concerns are illustrated, such as the way that anthropomorphism can influence people to believe that an AI system has obtained ‘sentience’, or other human characteristics.

Perhaps the most ambitious, closing section of the new work is the authors’ adjuration that the research and development community aim to develop ‘appropriate’ and ‘precise’ terminology, to establish the parameters that would define an anthropomorphic AI system, and distinguish it from real-world human discourse.

As with so many trending areas of AI development, this kind of categorization crosses over into the literature streams of psychology, linguistics and anthropology. It is difficult to know what current authority could actually formulate definitions of this type, and the new paper’s researchers do not shed any light on this matter.

If there is commercial and academic inertia around this topic, it could be partly attributable to the fact that this is far from a new topic of discussion in artificial intelligence research: as the paper notes, in 1985 the late Dutch computer scientist Edsger Wybe Dijkstra described anthropomorphism as a ‘pernicious’ trend in system development.

‘[A]nthropomorphic thinking is no good in the sense that it does not help. But is it also bad? Yes, it is, because even if we can point to some analogy between Man and Thing, the analogy is always negligible in comparison to the differences, and as soon as we allow ourselves to be seduced by the analogy to describe the Thing in anthropomorphic terminology, we immediately lose our control over which human connotations we drag into the picture.

‘…But the blur [between man and machine] has a much wider impact than you might suspect. [It] is not only that the question “Can machines think?” is regularly raised; we can —and should— deal with that by pointing out that it is just as relevant as the equally burning question “Can submarines swim?”’

However, though the debate is old, it has only recently become very relevant. It could be argued that Dijkstra’s contribution is equivalent to Victorian speculation on space travel, as purely theoretical and awaiting historical developments.

Therefore this well-established body of debate may give the topic a sense of weariness, despite its potential for significant social relevance in the next 2-5 years.

Conclusion

If we were to think of AI systems in the same dismissive way as organic Star Wars characters treat their own robots (i.e., as ambulatory search engines, or mere conveyers of mechanistic functionality), we would arguably be less at risk of habituating these socially undesirable characteristics over to our human interactions – because we would be viewing the systems in an entirely non-human context.

In practice, the entanglement of human language with human behavior makes this difficult, if not impossible, once a query expands from the minimalism of a Google search term to the rich context of a conversation.

Additionally, the commercial sector (as well as the advertising sector) is strongly motivated to create addictive or essential communications platforms, for customer retention and growth.

In any case, if AI systems genuinely respond better to polite queries than to stripped down interrogations, the context may be forced on us also for that reason.

* Even by 1983, the year that the final entry in the original Star Wars was released, fears around the growth of machine learning had led to the apocalyptic War Games, and the imminent Terminator franchise.

† Where necessary, I have converted the authors’ inline citations to hyperlinks, and have in some cases omitted some of the citations, for readability.

First published Monday, October 14, 2024

[novushitech]

Logistics and Road Transportation Services

Novus Hi Tech provides comprehensive logistics and road transportation services, specializing in efficient and reliable delivery solutions. With a focus on optimizing supply chains, they offer end-to-end logistics management, including freight forwarding, distribution, and inventory control. Their fleet of modern vehicles ensures timely and safe transportation of goods across various industries. Novus Hi Tech is committed to high standards of safety, flexibility, and customer service, ensuring seamless operations and tailored solutions to meet the specific needs of clients.

For more info visit our website:https://novushitech.com/

[ps1396262]

Autonomous Mobile Robots (AMRs) Market Size, Revenue Share, Drivers & Trends Analysis, 2024–2030

The Autonomous Mobile Robots Market was valued at USD 1.7 billion in 2023 and will surpass USD 5.2 billion by 2030; growing at a CAGR of 16.9% during 2024 – 2030. the Autonomous Mobile Robots (AMRs) market has seen significant growth, driven by advancements in robotics, artificial intelligence (AI), and machine learning. AMRs, which can navigate and perform tasks without direct human intervention, are transforming industries by enhancing efficiency, reducing costs, and improving safety. This blog explores the current state of the AMRs market, key trends, and future prospects.

Autonomous Mobile Robots are a type of robot that can perform various tasks in diverse environments, from warehouses and manufacturing floors to hospitals and retail spaces. Unlike traditional automated guided vehicles (AGVs), which require predefined paths and external guidance, AMRs use sensors, cameras, and AI to understand their surroundings, make decisions in real-time, and navigate dynamically within a space.

Read More about Sample Report: https://www.intentmarketresearch.com/request-sample/autonomous-mobile-robots-amrs-market-3605.html

Market Growth and Drivers

The AMRs market is experiencing rapid expansion, with a compound annual growth rate (CAGR) expected to exceed 20% over the next few years. Several factors contribute to this growth:

E-commerce Boom: The rise of e-commerce has led to an increased demand for efficient and flexible logistics solutions. AMRs help in automating warehouse operations, handling goods, and optimizing supply chains, making them indispensable in the fast-paced world of online retail.

Labor Shortages and Rising Costs: In many industries, labor shortages and rising wages are pushing companies to seek automated solutions. AMRs offer a viable alternative, performing repetitive tasks like material handling, inventory management, and transportation more cost-effectively than human labor.

Technological Advancements: Continuous improvements in AI, machine learning, and sensor technologies are enhancing the capabilities of AMRs. These advancements allow robots to operate in increasingly complex environments, boosting their adoption across various sectors.

Safety and Compliance: AMRs are designed to work alongside humans safely, reducing the risk of workplace accidents. In environments like healthcare, where precision and hygiene are critical, AMRs can perform tasks such as disinfection and delivery, minimizing human contact and contamination risks.

Key Trends Shaping the AMRs Market

Industry-Specific Solutions: As the AMRs market matures, we are witnessing the development of industry-specific solutions. For instance, in healthcare, AMRs are used for patient monitoring, medication delivery, and even surgical assistance. In manufacturing, they are employed for assembly line automation and quality control.

Integration with IoT and Big Data: The integration of AMRs with Internet of Things (IoT) devices and big data analytics is creating smarter, more connected environments. By collecting and analyzing data from their surroundings, AMRs can optimize their operations, predict maintenance needs, and adapt to changing conditions in real-time.

Collaborative Robots (Cobots): The rise of collaborative robots, or cobots, is another significant trend. Cobots are designed to work alongside human workers, assisting with tasks that require precision, strength, or endurance. This collaboration not only enhances productivity but also reduces the workload on human employees.

Expansion into New Markets: While logistics and manufacturing have been the primary markets for AMRs, their application is expanding into new areas such as agriculture, hospitality, and defense. In agriculture, for example, AMRs are used for tasks like crop monitoring, harvesting, and soil analysis.

Ask for Customization Report: https://www.intentmarketresearch.com/ask-for-customization/autonomous-mobile-robots-amrs-market-3605.html

Challenges and Future Outlook

Despite the promising growth, the AMRs market faces challenges, including high initial investment costs, regulatory hurdles, and the need for ongoing technological development. Ensuring that AMRs can operate safely and efficiently in diverse environments, particularly in industries with stringent regulations, remains a critical challenge.

Looking ahead, the future of the AMRs market is bright. As technology continues to advance, we can expect to see more sophisticated and versatile AMRs that can handle increasingly complex tasks. The integration of AMRs with other emerging technologies like 5G, edge computing, and autonomous vehicles will further propel the market forward.

Conclusion

The Autonomous Mobile Robots market is at the forefront of a technological revolution, reshaping how industries operate. From enhancing efficiency in warehouses to improving patient care in hospitals, AMRs are proving to be invaluable assets in the modern world. As the market continues to grow, driven by innovation and the need for automation, AMRs will play an increasingly important role in the future of work.

[andrewstech]

Discover the transformative capabilities of AMRs (Autonomous Mobile Robots), the cutting-edge technology revolutionizing multiple industries. With enhanced safety features and rapid execution, AMRs are surpassing traditional AGVs, reshaping workflows, and driving unparalleled efficiency."

[kirancmi]

Autonomous Mobile Robots Market Estimated To Witness Growth Due To Rising Demand From Logistics And Warehousing Industries

The global autonomous mobile robots market is estimated to be valued at US$ 3.41 Bn in 2024 and is expected to exhibit a CAGR of 3.1% over the forecast period 2024 to 2031, as highlighted in a new report published by Coherent Market Insights. Market Dynamics: The key driver explained from the heading is the rising demand from logistics and warehousing industries. The growing e-commerce sector has placed significant pressure on logistics and warehousing companies to expedite and streamline operations. Autonomous mobile robots help in automating material handling tasks which reduces operational costs and improves productivity for warehouse and logistics companies. Additionally, AMRs ensure safer working environments by eliminating risks associated with manual material handling. This factor is further driving their adoption across industries. Furthermore, continuous technological advancements are making AMRs more affordable and efficient. Emergence of IoT and AI-enabled AMR solutions is also fueling market growth over the forecast period. SWOT Analysis Strength: Autonomous mobile robots are highly efficient as they can operate 24/7 without breaks. They perform repetitive and routine tasks with high accuracy reducing the scope of human errors. Their programming makes them consistent in task performance. Weakness: High initial investment costs are required for deployment of autonomous mobile robots. Technical glitches and system failures can disrupt workflow. Lack of dexterity and adaptability are limitations as they cannot handle unpredictable situations or tasks requiring human judgment. Opportunity: Increased labor costs and shortage of labor is driving many industries to adopt robotics solutions. The logistics and warehousing sector offers huge growth opportunity for autonomous mobile robots for applications like transportation and sorting. Growth of e-commerce will further boost demand. Threats: Concerns around job losses can increase resistance from labor unions. Delay in development of technologies like advanced sensing, AI and 5G networks can hamper full potential of autonomous mobile robots. Changes in government regulations regarding robotics can affect adoption plans of some companies. Key Takeaways The global autonomous mobile robots market growth is expected to witness high growth over the forecast period owing to benefits like improved efficiency and reduced costs. The market size is estimated to reach US$ 3.41 Mn in 2024 from US$ 1.23 Mn in 2019, indicating a CAGR of around 3.1% during the period. Regional analysis:

North America currently dominates the market attributed to rapid technological advancement and increasing investments by prominent players in the region. Asia Pacific is anticipated to be the fastest growing market led by countries like China, Japan and India. With growing industrialization and manufacturing hub status, the APAC autonomous mobile robots market is projected to witness a CAGR of over 4% during the forecast period. Key players:

Key players operating in the autonomous mobile robots market are Sanofi, Pfizer, Inc., Novartis AG., B. Braun Melsungen AG, Fresenius Medical Care, Medtronic, Preservation Solution Inc., TransMedics, Inc., Organ Recovery Systems, and Transonic Systems Inc. These key players are focused on new product launches and partnerships to strengthen their market position.

Get more insights on this topic: https://www.newsstatix.com/the-autonomous-mobile-robots-market-growth-is-propelled-by-increasing-demand-for-automation-in-warehouses/

[buildwithrobots]

[kavithask]

Explore the world of Autonomous Mobile Robots (AMRs) in this concise overview. Discover how these intelligent machines are transforming industries like manufacturing and logistics, and find out how they are making our lives easier through applications in healthcare, transportation, and more. Dive into the technology behind AMRs and their potential impact on the future.

[taobotics]

Cargo handling has always been a time-consuming and unavoidable work, the emergence of AGV unmanned trucks, instead of people to complete the different states of the handling operation, greatly reduced people's labor intensity and improved the efficiency of the factory. The factory transportation robot system is based on a HandsFree robot and open source system, realizing the robot from map building, navigation, and motion control; it can autonomously and accurately complete the delivery of production materials under the operation scenario of human-machine mixing and provide the flexible flow of materials between production lines.

[john-godrej-koerber]

The Future of Logistics: Why Autonomous Mobile Robots (AMR) Are a Game-Changer

In today’s fast-paced world of logistics and warehousing, autonomous mobile robots (AMRs) are quickly becoming the cornerstone of efficient operations. As industries strive for faster, more reliable supply chains, these mobile robots are playing a crucial role in meeting the ever-growing demand for automation. From reducing human error to optimising storage space, AMR robots are revolutionising how goods are stored, picked, and delivered, creating smarter and more agile supply chain solutions.

What Are Autonomous Mobile Robots (AMRs)?

At their core, autonomous mobile robots are self-guided machines designed to transport goods within a warehouse or manufacturing facility without human intervention. Unlike traditional mobile robots, which require tracks or predefined paths, AMRs navigate using advanced sensors, cameras, and onboard mapping technology to move freely and adapt to their surroundings. These robots can pick, pack, and transport goods with high precision, eliminating the need for manual labour in repetitive tasks and significantly improving operational efficiency.

The Growing Role of AMR Robots in Warehousing

Warehouses have always been hubs of activity, packed with inventory, constant movement, and tight deadlines. However, the rise of autonomous mobile robots has brought a fresh wave of innovation, transforming how goods are handled within these spaces. With the ability to perform various tasks, such as transporting heavy pallets, picking items from shelves, and even unloading containers, AMR robots are drastically improving productivity in warehouses.

One of the key benefits of AMR robots is their adaptability. These robots are equipped with sensors and AI algorithms that enable them to understand and map their environment, allowing them to navigate complex, dynamic spaces without bumping into obstacles or creating inefficiencies. This level of intelligence gives mobile robots the ability to optimize routes in real-time, ensuring that goods are moved with minimal delays, while avoiding congestion in busy warehouses.

How AMR Robots Improve Operational Efficiency

The introduction of autonomous mobile robots has proven to deliver substantial cost savings and efficiency gains. Here's how they work their magic:

Increased Speed and Precision AMRs can carry out repetitive tasks like transporting goods at a much higher speed than humans, with fewer errors. Their precise operations minimise mistakes, improving overall order accuracy and reducing the need for costly rework.

24/7 Operation Unlike human workers who need breaks, sleep, and days off, an AMR robot can operate continuously, driving efficiency and throughput around the clock. They also work at a consistent pace, eliminating fluctuations in output that often occur in human-run warehouses.

Optimised Space Usage Traditional warehouses are often designed with wide aisles to accommodate human-operated forklifts and pallets. With autonomous mobile robots, the need for large aisles is eliminated, as these robots can maneuver through narrower spaces, allowing more inventory to be stored in the same physical footprint. This leads to more effective use of warehouse space and, ultimately, greater storage capacity.

Reduced Labour Costs By automating tasks that were traditionally manual, mobile robots help reduce the dependency on human labour for low-value tasks. This allows human workers to focus on higher-value activities, like strategic planning and quality control, while the robots handle the heavy lifting.

How AMR Robots Support the Future of E-Commerce

The rise of e-commerce has drastically shifted consumer expectations, with customers demanding faster deliveries and better service than ever before. This is where autonomous mobile robots come into play. With AMR systems handling much of the physical labour within warehouses, e-commerce businesses can streamline their order fulfilment processes, accelerating the speed at which products are picked, packed, and shipped.

In addition to enhancing speed, AMR robots ensure better accuracy and consistency. This is crucial in the e-commerce industry, where one mistake in fulfilling an order can lead to customer dissatisfaction, returns, or lost revenue. By implementing mobile robots that are programmed to follow precise guidelines and workflows, e-commerce businesses can drastically reduce order errors and improve overall customer experience.

The Future of AMR Robots in Industry

As we move further into an age dominated by smart technology, the role of autonomous mobile robots is only expected to grow. With advancements in AI, machine learning, and real-time data processing, future AMRs will become even more efficient and intelligent. They will be able to perform even more complex tasks, such as sorting and categorising inventory or managing the entire supply chain from start to finish.

The potential applications of mobile robots extend beyond just warehouses. Industries like manufacturing, retail, and healthcare are already exploring the integration of AMR systems into their operations. From assembly lines to patient transport, the possibilities for autonomous mobile robots are endless.

A Smarter, More Efficient Future

The rise of autonomous mobile robots marks a significant shift in how logistics and supply chain operations are run. By improving speed, accuracy, safety, and scalability, the AMR robot is changing the game for businesses of all sizes. As these robots continue to evolve, we can expect them to play an even larger role in shaping the future of industries worldwide, driving efficiencies and unlocking new levels of productivity.

[jcmarchi]

Pavlo Pikulin, Founder & CEO of Deus Robotics – Interview Series

New Post has been published on https://thedigitalinsider.com/pavlo-pikulin-founder-ceo-of-deus-robotics-interview-series/

Pavlo Pikulin, Founder & CEO of Deus Robotics – Interview Series

Pavlo Pikulin is the founder and CEO of Deus Robotics, which has developed an AI platform that connects and enhances the intelligence of warehouse robots from any manufacturer. The company also offers AI-powered robots that cover 90% of warehouse automation needs — and counting. With over 22 years of experience in AI and 6 years in robotics, Pavlo serves as an Expert on the Artificial Intelligence committee under Ukraine’s Ministry of Digital Transformation.

Can you share your journey in AI and robotics, and what inspired you to start Deus Robotics?

It all began with my dad, who’s always been a tech enthusiast. Even before I was born, he got me a personal computer — pretty rare in my hometown back in 1989.

When I was five, I wrote my first computer program. The idea of giving a task to a machine and watching it execute was absolutely fascinating to me.

At seven, I sold my first website for $20. Soon after, I started building and selling computers. By thirteen, I had written a program to bypass a captcha in a computer game, which later evolved into an automatic number-plate recognition system.

By fifteen, I was convinced that the future was all about robotics.

This realization set my path towards robotics and AI. However, at that age, I didn’t have the means to start my own robotics company, so I took a bit of a detour. At nineteen, I launched a game studio which grew into a global company with 60 million users worldwide. By 2021, we had 700 employees, and some of our games became the top downloads in their genre in the US.

But robotics was always on my mind and in my heart. I’ve always believed the world would be better if robots could handle all the tough, mundane, or dangerous tasks. By late 2017, I had saved enough to finally bootstrap my own robotics company and make that vision a reality.

It took me a year to do all the research in robotics I needed to start. After that, I gathered a team of incredibly talented engineers and programmers — some old friends, others new faces — and we launched Deus Robotics in early 2019. This past summer, Deus Robotics was shortlisted for Logistics UK’s Logistics Awards, Robotics & Automation Awards, and Supply Chain Excellence Awards USA.

What lessons did you carry over from your 15 years in the gaming industry to robotics and AI?

Working on games has given me valuable experience in many key areas, and it’s been rewarding to see how these skills apply to robotics.

Virtual Worlds for Robotics

Virtual worlds are a game-changer in robotics, offering a quicker and more efficient way to test ideas without waiting months for a hardware prototype. Instead of spending time and resources on physical prototypes, you can experiment in a virtual environment. Creating these virtual worlds is a lot like designing a game, where robots interact with their surroundings — this is where my game development experience really comes in handy.

Algorithm Transfer

When we were developing algorithms for robot path planning, as a team, we tapped into our experience from creating similar algorithms in games for character navigation. In our strategy games, hundreds of characters had to navigate through cities with roads and buildings — just like robots in our systems. This made transferring our path-planning expertise to robotics feel seamless and natural.

Complex Software and Analytics

Robots, much like games, are built on complex software. Developing a world-class game involves creating secure payment systems, social features like chat and groups, competitive elements, and a detailed virtual world with countless mechanics. One of our games had over 300 functional windows — more than you’d find in most banking apps! Games also handle massive loads, with millions or even billions of users performing countless actions, and this experience provides valuable insights for warehouse robotics.

Another crucial aspect is analytics. In games, we had to quickly and efficiently analyze user actions, managing high volumes of data. The same is true for robots, which continuously send vast amounts of data that need robust processing and analysis systems. Additionally, creating AI agents in games to engage players is similar to programming robots, as both involve crafting intelligent, responsive behavior.

In short, if you can build and manage a game development team, you’ve got what it takes to lead a robotics team as well.

How has your role in the Artificial Intelligence Committee under Ukraine’s Ministry of Digital Transformation influenced your work at Deus Robotics?

The Committee’s goal is to advise government authorities on AI, including robotics. I joined to provide expertise specifically in robotics and to consult on government requests. We’re also focused on education, regulations, and pilot AI projects in Ukraine. 

Through my work with the Committee, Deus Robotics found a way to expand our passion for advancing robotics in Ukraine beyond just warehouse automation. This allows us to make a broader impact.

Could you explain the unique AI brain developed by Deus Robotics and how it enhances the intelligence of warehouse robots?

Our robot control software, dubbed AI brain, includes key technologies:

1. On-Robot Systems:

A system that collects and analyzes data from all the robot’s sensors, helping it understand its surroundings, determine its location, and make decisions.

A control system that manages all robot mechanisms, such as manipulators, motors, lidars, and cameras, to execute the robot’s decisions.

A 3D recognition system that identifies obstacles using 3D cameras and a lidar recognition system that interprets what the LIDAR detects.

2. Centralized Management Platform:

Our AI platform connects all robots via Wi-Fi, coordinating their actions and enabling centralized communication.

In warehouses, our centralized system is crucial. It prevents collisions by tracking each robot’s exact location in real-time, allowing them to move quickly and safely.

This centralized system also integrates seamlessly with the warehouse management system, making it a key advantage and streamlining robot management.

Besides being connected, our robots are also getting smarter. Thanks to the adapters for different robots, our system can integrate robots from various manufacturers, enabling them to share information and coordinate tasks.

Previously, robots could only coordinate with other robots from the same manufacturer. Now, they can exchange data and work together across different brands.

What sets Deus Robotics apart from other companies in the warehouse automation industry?

Unlike other warehouse robotics companies, we’ve developed the heart of what makes robots truly effective: their brain. Our AI-powered brain connects with robots from any manufacturer, including our own, turning even the simplest robots into smarter, more capable machines. This kind of interoperability is something special in the industry.

This is especially important because, typically, robots from different manufacturers don’t play well together. Each robotics provider only covers a small slice of automation needs, leaving warehouses to choose from too many options. Each provider also requires costly and time-consuming integration, making it hard to switch if you want to try something new. Plus, when robots from different providers can’t connect or be centrally managed, it complicates operations and limits your ability to scale.

That’s where we come in. Our system makes it easy to bring as many robots as you need under one roof, all managed through a single, user-friendly platform.

With our solution, you get:

All automation needs covered under one system.

A single integration for all current and future providers, eliminating repeated integration costs and allowing you to switch providers as needed.

An easy-to-use management system for all current and future robots.

AI-enhanced, smarter robots that work together seamlessly (what’s important, our system can connect with humanoids, too).

Ongoing training and support for warehouse operators to ensure smooth operations.

And the best part? Our solution is truly all-in-one. We offer robots that tackle 90% of logistics tasks (and counting), paired with our AI platform that ties everything together. With our system, you can easily connect robots from any provider, simplify your operations, and scale your automation like never before. This is particularly important as only 20% of warehouses are automated.

How does Lidar technology enhance the navigation capabilities of your AGVs compared to traditional methods?

When our robot spots a floor tag, it navigates with pinpoint accuracy — within 1mm. But when the tag isn’t in view, accuracy can drop to around 20mm. That’s where LIDAR comes in, helping to keep navigation precise even between markers.

LIDAR adds another layer of information, which we combine with data from tags and gyroscopes. Each source gives us different insights with varying accuracy. Our specialized system merges all these inputs to pinpoint the robot’s position with high precision. The more accurate the data, the better the robot navigates, and precise positioning is key to smooth and effective robot movement.

Could you describe the role and benefits of your Robot as a Service (RaaS) and Software as a Service (SaaS) models for businesses?

Buying robots requires significant capital investment, leading to a payback period of one to three years. This also ties up the client’s operating funds and increases capital expenses.

RaaS (Robots as a Service) is a game-changer for businesses. It eliminates the need for capital investment, relying instead on operational expenses. The payback begins in the first month, thanks to the immediate boost in productivity. Instead of needing 2-5 times more people to achieve the same productivity, robots enhance the efficiency of existing staff—at a lower cost than hiring additional workers.

Plus, RaaS reduces risk. There’s no need to freeze investments, and expenses shift from CAPEX to OPEX.

What are the advantages of QR Code Navigation in AGVs, and how does it compare to Lidar?

Automated guided vehicles (AGVs) follow fixed routes, navigating via floor tags instead of LIDAR, and can’t deviate from their path. In contrast, our autonomous mobile robots (AMRs) use 3D LIDAR scans for flexible navigation without relying on floor markers.

In what ways do Deus Robotics’ solutions address the current challenges faced by warehouse logistics and the 3PL industry?

Currently, we offer a solution that transports goods from point A to point B, which is especially appealing to fulfillment centers. However, the need to move goods exists in any warehouse — whether it’s in manufacturing, healthcare, automotive, or retail. In the future, we plan to expand our product line to include robots that can handle tasks like packing, loading and unloading trucks, unpacking, and picking. We’re already working closely with robot manufacturers to integrate their products into our lineup.

Another challenge we’re addressing to make warehouses more efficient is providing a unified system for managing robots — a single integration, management, and enhancement point. Our clients don’t need to deal with multiple robot platforms. They only need to integrate with us once and can then use any robots they choose. While our current selection of robots is limited (we have 15 models to date), we’re constantly working to expand it.

What advancements do you foresee in the integration of AI and robotics in warehouse automation over the next 5-10 years?

One of the biggest challenges we face is figuring out the best way to automate each warehouse. Even though warehouses perform similar tasks, they differ in the details — like processes, staff, the types of goods they handle, and their goals. Some aim for maximum efficiency, others for cost-effectiveness. Planning the right automation solution and setting up the best business processes takes a lot of time and effort from experts. I’m convinced that AI will soon help us design warehouse automation in just seconds, making the process much smoother and more efficient.

Another exciting development is the rise of specialized robots designed for specific tasks. While the first robots were built for general use, as automation grows, we’ll see more robots tailored to unique needs. For example, inventory robots are just starting to appear since most warehouses only need one or two.

Humanoid robots are also on the horizon. These versatile robots will be able to handle tasks much like humans, thanks to advances in AI.

AI is also getting better at helping people with their tasks, like smarter voice assistants that can offer guidance. Plus, AI can optimize warehouse operations by analyzing data and improving efficiency. With access to digital warehouse data, AI can quickly identify and fix issues, making everything run more smoothly.

Looking at the bigger picture, AI will also improve how different warehouses work together, along with suppliers and logistics partners. This includes better scheduling, moving goods efficiently, and predicting what will be needed next.

All in all, AI and robotics are not just tools for automation — they’re the keys to unlocking a smarter, more connected future for warehouses and beyond.

Thank you for the great interview, readers who wish to learn more should visit Deus Robotics.

[novushitech]

Smart Factory System

Novus Hi Tech's Smart Factory System integrates advanced technologies like IoT, AI, and automation to optimize manufacturing processes. This system enables real-time monitoring, data analysis, and predictive maintenance, resulting in enhanced efficiency, reduced downtime, and improved product quality. By leveraging interconnected devices and intelligent analytics, Novus Hi Tech's solution supports seamless operations, smart decision-making, and cost-effective production, aligning with Industry 4.0 standards.

[amrutmnm]

How AI is Transforming Unmanned Systems

The Unmanned Systems Market is undergoing a significant transformation, driven by rapid advancements in Artificial Intelligence (AI). AI-powered autonomous systems are enhancing the capabilities of drone technology, robotic warfare, urban air mobility, drone logistics and transportation, and unmanned traffic management. AI integration is revolutionizing surveillance, reconnaissance, and defense operations while streamlining commercial applications such as agriculture, logistics, and industrial automation.

The Global Unmanned Systems Market size was valued at USD 27.13 billion in 2024 and is projected to reach USD 43.54 billion by 2030, growing at a CAGR of 8.2%. In volume, the market is set to expand from 1,998,009 units in 2024 to 2,876,197 units by 2030. As AI continues to drive efficiency, autonomy, and security, the demand for unmanned systems is expected to surge across various industries.

The Role of AI in the Growth of the Unmanned Systems Market

AI is a key enabler in advancing unmanned systems, allowing machines to operate with minimal human intervention. These advancements are transforming multiple sectors, especially defense, where AI-driven autonomous systems are being deployed for critical missions.

1. AI in Defense and Robotic Warfare

AI-powered unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) are significantly enhancing intelligence, surveillance, and reconnaissance (ISR) capabilities. Modern warfare demands real-time data processing and precision targeting, which AI-based autonomous systems can efficiently execute.

Drones like the MQ-9 Reaper and RQ-4 Global Hawk use AI to track, identify, and neutralize threats autonomously. Robotic warfare is reshaping battlefield strategies by reducing human casualties and increasing mission effectiveness. AI-powered EO/IR sensors, radars, and synthetic aperture radars (SARs) help unmanned systems operate in complex terrains, boosting their strategic value in military operations.

2. AI in Drone Technology and Urban Air Mobility

The application of AI-driven drone technology is expanding beyond military use. In urban air mobility (UAM), AI is enabling the development of autonomous air taxis and delivery drones, addressing congestion and revolutionizing transportation logistics. AI helps optimize flight paths, manage unmanned traffic management (UTM) systems, and improve operational safety.

As cities move toward smart mobility solutions, AI-driven autonomous systems will play a crucial role in enhancing urban transportation networks. This technology will reduce human errors, lower operational costs, and support eco-friendly solutions for drone logistics and transportation.

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Challenges in AI Adoption for the Unmanned Systems Market

1. Information Security Risks and Cybersecurity Concerns

The rapid integration of AI in unmanned systems has raised serious concerns about data security and cybersecurity threats. AI-powered drones and autonomous systems handle sensitive information, making them prime targets for cyberattacks.

Unauthorized access to AI-driven unmanned systems could compromise military operations, leading to mission failures and security breaches. Intercepted UAV data could provide adversaries with critical intelligence, impacting national security. Addressing these risks requires stringent cybersecurity measures, encryption protocols, and AI-driven threat detection systems.

2. Regulatory Complexities and Compliance Issues

AI-driven unmanned systems operate across international borders, making regulatory compliance a significant challenge. Countries have different regulations governing drone operations, data privacy, and airspace management, creating barriers for businesses looking to deploy autonomous systems globally.

The absence of a unified regulatory framework complicates the adoption of AI-powered drones for commercial and defense applications. For instance, drone operators must adhere to different flight altitude restrictions, operational guidelines, and licensing requirements in each country. Resolving these challenges will require international cooperation and harmonized AI governance policies.

AI-Powered Opportunities in the Unmanned Systems Market

1. Growing Defense Budgets and AI-Driven Military Investments

With rising global defense budgets, governments are heavily investing in AI-powered unmanned systems to enhance national security and operational efficiency. AI-driven UAVs and UGVs are now essential in modern defense strategies, offering real-time surveillance, precision strikes, and autonomous combat support.

The US military and NATO allies are at the forefront of AI integration, leveraging autonomous drones for border security, maritime patrols, and counterterrorism operations. Countries worldwide are increasing their defense expenditures, making AI-powered unmanned systems a lucrative market segment.

2. AI in Commercial Drone Applications

The demand for AI-powered drone technology is rising across commercial sectors such as agriculture, logistics, and infrastructure monitoring. AI-enhanced unmanned systems are streamlining supply chain operations, reducing human intervention, and optimizing last-mile deliveries.

Drone logistics and transportation are witnessing rapid adoption in e-commerce and retail, as AI-powered UAVs reduce delivery times and costs. Similarly, AI-driven drones in agriculture are improving crop monitoring, precision farming, and automated pesticide spraying.

3. AI-Driven Enhancements in Power Efficiency and Endurance

One of the primary challenges in the unmanned systems market is the limited endurance of battery-powered drones and autonomous vehicles. AI is helping overcome this issue by optimizing energy consumption, flight paths, and power management systems.

Advanced AI-based battery management algorithms are extending the operational life of autonomous systems, enabling longer surveillance missions, enhanced drone logistics, and improved battlefield operations. The integration of AI with renewable energy solutions, such as solar-powered UAVs, is further pushing the boundaries of endurance and efficiency.

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Regional Market Analysis: North America Leads AI Integration

North America is poised to be the largest market for AI-driven unmanned systems, fueled by increasing defense investments, technological advancements, and commercial drone adoption. The United States is leading the AI revolution, with Lockheed Martin, Northrop Grumman, Boeing, and General Dynamics at the forefront of innovation.

The integration of AI, machine learning, and advanced sensors is enhancing the operational capabilities of unmanned systems in North America. Key industry players are focused on developing next-generation autonomous solutions for defense, logistics, and urban air mobility applications.

Future of AI in the Unmanned Systems Market

AI will continue to reshape the unmanned systems market, unlocking new possibilities for defense, commercial, and industrial applications. The future will see increased autonomy, reduced human intervention, and enhanced security in autonomous systems.

As AI-driven drone technology advances, unmanned traffic management will become a critical component of smart cities, enabling seamless urban air mobility and logistics networks. The integration of AI-powered robotics in warfare will further enhance military capabilities and mission success rates.

While challenges such as cybersecurity risks and regulatory hurdles remain, continuous AI innovation will drive the growth of the unmanned systems market, making it a cornerstone of the global technological revolution.

[a1medianet]

AI & Robotics: The Rise of Self-Driving Cars & Robotaxis

📅 Timeline: 2025-2026 🏢 Key Players: Tesla, OpenAI, Google DeepMind

AI advancements are skyrocketing in 2025, with Tesla’s Full Self-Driving (FSD) technology reaching new heights. This year, we’re expecting:

🚗 Tesla’s first fully autonomous robotaxi fleet 🤖 AI-powered assistants integrated into daily life ⚡ Breakthroughs in machine learning for better decision-making

With AI becoming smarter and more efficient, these innovations will reshape transportation, business, and everyday life.

Watch on YouTube: https://youtube.com/shorts/T5vKveiYHI4

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These 7 Innovations Will Change Humanity Forever https://www.youtube.com/watch?v=L6W-eaB7PEY&t

Which of these innovations excites you the most? Let us know in the comments!

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