Robotics and AI Integration

'A roadmap for AI in robotics' - our latest article (https://rdcu.be/euQNq) published in Nature Machine Intelligence, offers an assessment of what artificial intelligence (AI) has achieved for robotics since the 1990s and proposes a research roadmap with challenges and promises. Led by Aude G. Billard, current president of IEEE Robotics and Automation Society, this perspective article discusses the growing excitement around leveraging AI to tackle some of the outstanding barriers to the full deployment of robots in daily lives. It is argued that action and sensing in the physical world pose greater and different challenges for AI than analysing data in isolation and therefore it is important to reflect on which AI approaches are most likely to be successfully applied to robots. Questions to address, among others, are how AI models can be adapted to specific robot designs, tasks and environments. It is argued that for robots to collaborate effectively with humans, they must predict human behaviour without relying on bias-based profiling. Explainability and transparency in AI-driven robot control are essential for building trust, preventing misuse and attributing responsibility in accidents. Finally, the article close with describing the primary long-term challenges, namely, designing robots capable of lifelong learning, and guaranteeing safe deployment and usage, as well as sustainable development. Happy to be co-author of this great piece led by Aude G. Billard, with contributions from Alin Albu-Schaeffer, Michael Beetz, Wolfram Burgard, Peter Corke, Matei Ciocarlie, Danica Kragic, Ken Goldberg, Yukie NAGAI, and Davide Scaramuzza Nature Portfolio IEEE #robotics #robots #ai #artificial #intelligence #sensors #sensation #ann #roadmap #generativeai #learning #perception #edgecomputing #nearsensor #sustainability

When many people think of robots paired with AI, their first thought is often of militarized or law-enforcement machines, raising questions about how they’d distinguish combatants from civilians. That’s a legitimate concern - after all, accuracy in identifying targets can have life-or-death consequences if misused. However, the potential applications for this technology extend far beyond guns and military hardware. Beyond the Battlefield - Everyday Use Cases - Social Media & Content Creation: Imagine a gimbal that not only stabilizes your camera but intelligently tracks your face and adjusts focus and angles to achieve professional-quality shots. It could transform how influencers, marketers, and everyday users create content for platforms like Instagram or TikTok, eliminating the need for a dedicated videographer. - Medical and Assistive Robotics: AI-guided robotic arms can aid surgeries with sub-millimeter precision, reducing errors and helping surgeons perform complex procedures more safely. Similarly, in rehabilitation or eldercare settings, robots can assist in physical therapy, monitoring patient movements to ensure correct form and track recovery progress. - Agricultural Automation: Robots and AI can be used on farms to detect weeds, monitor crop health, and apply resources like water or fertilizer with pinpoint accuracy - improving yields and reducing chemical usage. Ethical Concerns - Accuracy vs. Oversight: Even the most advanced AI can misidentify targets or features under unpredictable conditions. Ensuring human oversight or strict compliance with safety standards is crucial. - Bias in AI: AI models learn from data. If the training data is incomplete or biased, errors can occur. It’s not just about “friend vs. foe” - it could also be about misunderstanding cultural nuances or misreading human actions. - Regulatory Frameworks: To mitigate misuse, industry standards and regulations should address how these systems are developed, deployed, and monitored. Transparency regarding data collection, usage policies, and accountability will help build trust. The synergy of AI and robotics is powerful, promising to improve daily tasks from content creation to medical procedures - far from the battlefield concerns many imagine. Balancing innovation with ethical responsibility is the tightrope we’ll continue walking. With robust oversight, transparent design, and a commitment to responsible deployment, we can harness these technologies for good, while minimizing risks related to discrimination, misuse, or harm. What’s your take? Can we steer AI-driven robots toward beneficial applications without ignoring the dangers of militarization or misuse? #innovation #technology #future #management #startups

𝐄𝐦𝐛𝐨𝐝𝐢𝐞𝐝 𝐀𝐈: 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 Embodied artificial intelligence refers to the integration of AI systems into physical machines, emphasizing the emergence of intelligence through interaction with the environment. 🎯𝐊𝐞𝐲 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬 ▪Intelligence is not solely abstract computation ▪Physical form and environmental interaction are crucial ▪Sensory input and real-world adaptation are essential 🎯𝐇𝐢𝐬𝐭𝐨𝐫𝐢𝐜𝐚𝐥 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 ▪Builds on the concept of embodied intelligence ▪Popularized by researchers like Rodney Brooks ▪Marks a shift from traditional symbolic AI approaches 🎯𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 ▪𝐀𝐠𝐢𝐥𝐞 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬: Boston Dynamics' Spot and Atlas robots ▪𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐕𝐞𝐡𝐢𝐜𝐥𝐞𝐬: Self-driving cars with real-time environmental processing ▪𝐇𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐑𝐨𝐛𝐨𝐭𝐬: Tesla's Optimus and Figure AI's prototypes for human-like tasks 🎯𝐌𝐞𝐚𝐬𝐮𝐫𝐢𝐧𝐠 𝐄𝐦𝐛𝐨𝐝𝐢𝐞𝐝 𝐀𝐈 ▪Adaptability to new situations ▪Physical performance in object manipulation and navigation ▪Sensorimotor integration efficiency ▪TOPS (𝐓𝐫𝐢𝐥𝐥𝐢𝐨𝐧𝐬 𝐨𝐟 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐏𝐞𝐫 𝐒𝐞𝐜𝐨𝐧𝐝) as a computational metric 🎯𝐈𝐦𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 ▪𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭: More sophisticated and capable robots ▪𝐀𝐈 𝐄𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Bridging abstract AI with practical, real-world applications ▪𝐇𝐮𝐦𝐚𝐧-𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧: Improved interfaces and collaboration ▪𝐓𝐚𝐬𝐤 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: Enhanced capabilities in complex, physical environments 🎯𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 ▪Achieving general adaptability comparable to human intelligence ▪Balancing task-specific excellence with broader cognitive abilities ▪Addressing ethical considerations in real-world AI applications Embodied AI represents a critical frontier in robotics and AI, promising to narrow the gap between artificial and human intelligence while revolutionizing how machines interact with the physical world. 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/ghAxWtZc #AI #DigitalTransformation #GenerativeAI #GenAI #Innovation  #ArtificialIntelligence #ML #ThoughtLeadership #NiteshRastogiInsights  ---------------------------------------------------------------------- • Please 𝐋𝐢𝐤𝐞, 𝐒𝐡𝐚𝐫𝐞, 𝐂𝐨𝐦𝐦𝐞𝐧𝐭, 𝐒𝐚𝐯𝐞, 𝐅𝐨𝐥𝐥𝐨𝐰 https://lnkd.in/gcy76JgE

🌟 While AI's impact on software is widely recognized, robotics is making strides just as impressive—often under the radar. The next big investment opportunities will be at the crossroads of Robotics and AI. As a VC, are you prepared to explore this dynamic fusion? 🔍 For instance, Google DeepMind has recently unveiled an AI-powered robot that achieves amateur human-level performance in table tennis. 🤖🏓 As a VC investor, I'm closely watching this convergence because the potential is massive. Here are a few key areas where the fusion of AI and robotics can create significant value: Healthcare: Imagine robots with advanced AI assisting in surgeries, rehabilitation, and patient care, enhancing precision and personalization in medical services. Manufacturing: AI-driven robots can revolutionize production lines, improving automation, quality control, and flexibility in manufacturing processes. Logistics: In warehousing and supply chains, AI-enabled robots can optimize sorting, packing, and inventory management, leading to greater efficiency and cost savings. Consumer Products: From smart home devices to personal assistants, AI-powered robots can make daily life more convenient and tailored to individual needs. Agriculture: AI and robotics can transform farming with automated planting, harvesting, and crop monitoring, supporting more sustainable and efficient agricultural practices. If you're working on a startup at the forefront of this exciting intersection, I’d love to hear about the unique challenges you’re addressing and how your technology integrates AI and robotics to solve them. The opportunities in this space are immense, and I’m eager to explore potential collaborations and investments that could drive the next wave of innovation. #AI #Robotics #Innovation #Investment #FutureOfTech #VC #ArtificialIntelligence

Hello 👋 from the Automate Show in downtown Detroit. I’m excited to share with you what I’m learning. Robotics is undergoing a fundamental transformation, and NVIDIA is at the center of it all. I've been watching how leading manufacturers are deploying NVIDIA's Isaac platform, and the results are staggering: Universal Robotics & Machines UR15 Cobot now generates motion faster with AI. Vention is democratizing machine motion for businesses. KUKA has integrated AI directly into their controllers. But what's truly revolutionary is the approach: 1. Start with a digital twin In simulation, companies can deploy thousands of virtual robots to run experiments safely and efficiently. The majority of robotics innovation is happening in simulation right now, allowing for both single and multi-robot training before real-world deployment. 2. Implement "outside-in" perception Just as humans perceive the world from the inside out, robots need their own sensors. But the game-changer is adding "outside-in" perception - like an air traffic control system for robots. This dual approach is solving industrial automation's biggest challenges. 3. Leverage generative AI Factory operators can now use LLMs to manage operations with simple prompts: "Show me if there was a spill" or "Is the operator following the correct assembly steps?" Pegatron is already implementing this with just a single camera. They're creating an ecosystem where partners can integrate cutting-edge AI into existing systems, helping traditional manufacturers scale up through unprecedented ease of use. The most powerful insight? Just as ChatGPT reached 100 million users in 9 days, robotics adoption is about to experience its own inflection point. The barriers to entry are falling. The technology is becoming accessible even for mid-sized and smaller companies. And the future is being built in simulation before transforming our physical world. Michigan Software Labs Forbes Technology Council Fast Company Executive Board

Path Robotics’ Sales Surge—Here’s the Smart AI Strategy Behind It Path Robotics is redefining robotic welding with AI-driven automation, pushing the limits of what robots can do in unstructured environments. Instead of relying solely on pre-programmed instructions, Path’s robots learn and adapt—an approach that’s resonating with manufacturers looking to automate complex tasks. Andrew Lonsberry, CEO of Path Robotics, recently made a compelling argument about why real-world data is essential to overcoming the limitations of simulation in robotics training. He explains: “The best simulation software in the world still isn’t good enough. Today’s sims miss the real-world edge cases—the rare, unpredictable failures that make or break system performance in production environments.” Rather than relying only on simulations, Path Robotics is incorporating real-world data to refine its AI models. Their robots don’t just train in a simulated world—they learn from actual deployments, continuously improving through real feedback. This approach bridges the “sim-to-real” gap and builds a more reliable and adaptable robotic system. It’s clearly working. Path’s sales are surging, proving that they’ve hit on the right strategy. When real-world results matter, Path is showing how AI-powered robotics can truly deliver. Andrew's Post: https://lnkd.in/ezj2xjfk ATI Industrial Automation supports robotic AI through advanced force sensing, helping resolve tough manufacturing challenges and further advancing intelligent automation. #robotics

The Convergence of Intelligent Technologies: Shaping the Autonomous Future pt.1 We are at the dawn of a technological revolution where the convergence of intelligent technologies is reshaping industries and societies. In a 2023 Forbes article I co-authored with Sarwant Singh, we explored the rise of the ‘Autonomous World’—a world powered by hyper-connectivity, intelligent machines, and continuous innovation. Today, these shifts are accelerating, driven by advances in AI, robotics, edge computing, and interconnected networks. FROM HARDWARE TO SOFTWARE INTEGRATION IN ROBOTICS Historically, robotics innovation has been centered around hardware improvements in motors, sensors, and physical components. However, as hardware matures and becomes commoditised, the future of robotics is moving toward software-driven intelligence. AI, machine vision, and multi-agent orchestration platforms now empower fleets of diverse robots—ranging from drones to forklifts—to navigate unpredictable environments and collaborate in real time. While software is leading this new wave, custom hardware remains critical for high-stakes industries such as healthcare, defense, and advanced manufacturing, where performance, reliability, and durability cannot be compromised. EDGE AI: BRINGING INTELLIGENCE CLOSER TO THE SOURCE AI is also evolving from cloud-reliant systems to intelligent, edge-based operations. As NVIDIA CEO Jensen Huang highlighted at GTC 2025, the future of AI is not just about generating data—it’s about enabling physical AI, where embodied machines learn, reason, and act autonomously. Edge AI brings these capabilities closer to the source, improving data security, reducing costs, and enabling real-time decision-making without relying on the cloud. This shift is crucial as enterprises strive to scale AI securely and efficiently across various industries, including logistics, mining, healthcare, and finance. THE HUMAN FACTOR: AUGMENTING, NOT REPLACING A key misconception is that autonomous technologies will replace humans. In reality, they are designed to augment human capabilities, reduce operational risks, and create new opportunities for reskilling and higher-value work. As these technologies take over hazardous or repetitive tasks, they can extend the working life of an aging workforce, support diversity, and improve work-life balance. However, this requires ethical foresight and leadership that embraces system thinking—integrating AI, robotics, human capital, and sustainability into a holistic strategy. Part 2 of this post series will explore the power of converging S-curves, which illustrate how various technological advancements interlink and complement one another to create connected ecosystems and drive further innovation. #autonomy #intelligenttech #convergence

In a recent post about Oshkosh’s AI journey, I was asked how I see AI integrated into other digital technologies like robotics and IIoT.    At Oshkosh, we see a close correlation between cognitive and physical automation through AI. We are advancing our cognitive and physical automation journey in parallel. AI driven smart robots apply the perfect amount of paint on our machines and cobots like automated guided vehicles are using real-time data to navigate the shop floor, along with the potential of fully intelligent humanoid support. The connection of cognitive and physical automation with AI helps develop an intelligent enterprise that optimizes both human and machine capabilities. Continuing to embrace the partnership between AI and team members will drive smarter, more responsive operations across the value chain.    #dataanalytics #AIjourney #generativeAI #advancedanalytics #digitaltransformation #datascience