Applications of Mobile and Intelligent Robots

Yesterday, we explored Synthetic Interoception and how robots might gain self-awareness. Today, we shift focus to physical intelligence: how robots can achieve the touch and finesse of human hands. Rigid machines are precise but lack delicacy. Humans, on the other hand, easily manipulate fragile objects, thanks to our bodies' softness and sensitivity. Soft-body Tactile Dexterity Systems integrate soft, flexible materials with advanced tactile sensing, granting robots the ability to: ⭐ Adapt to Object Shapes: Conform to and securely grasp items of diverse forms. ⭐ Handle Fragile Items: Apply appropriate force to prevent damage. ⭐ Perform Complex Manipulations: Execute tasks requiring nuanced movements and adjustments. Robots can achieve a new level of dexterity by emulating the compliance and sensory feedback of human skin and muscles. 🤖 Caregiver: A soft-handed robot supports elderly individuals and handles personal items with gentle precision. 🤖 Harvester: A robot picks ripe tomatoes without bruising them in a greenhouse, using tactile sensing to gauge ripeness. 🤖 Surgical Assistant: In the OR, a robot holds tissues delicately with soft instruments, improving access and reducing trauma. These are some recent relevant research papers on the topic: 📚 Soft Robotic Hand with Tactile Palm-Finger Coordination (Nature Communications, 2025): https://lnkd.in/g_XRnGGa 📚 Bi-Touch: Bimanual Tactile Manipulation (arXiv, 2023): https://lnkd.in/gbJSpSDu 📚 GelSight EndoFlex Hand (arXiv, 2023): https://lnkd.in/g-JTUd2b These are some examples of translating research into real-world applications: 🚀 Figure AI: Their Helix system enables humanoid robots to perform complex tasks using natural language commands and real-time visual processing. https://lnkd.in/gj6_N3MN 🚀 Shadow Robot Company: Developers of the Shadow Dexterous Hand, a robotic hand that mimics the human hand's size and movement, featuring advanced tactile sensing for precise manipulation. https://lnkd.in/gbpmdMG4 🚀 Toyota Research Institute's Punyo: Introduced 'Punyo,' a soft robot with air-filled 'bubbles' providing compliance and tactile sensing, combining traditional robotic precision with soft robotics' adaptability. https://lnkd.in/gyedaK65 The journey toward widespread adoption is progressing: 1–3 years: Implementation in controlled environments like manufacturing and assembly lines, where repetitive tasks are structured. 4–6 years: Expansion into dynamic healthcare and domestic assistance settings requiring advanced adaptability and safety measures. Robots are poised to perform tasks with unprecedented dexterity and sensitivity by integrating soft materials and tactile sensing, bringing us closer to seamless human-robot collaboration. Next up: Cognitive World Modeling for Autonomous Agents.

𝗪𝗵𝗲𝗻 𝗔𝗜 𝗚𝗲𝘁𝘀 𝗮 𝗕𝗼𝗱𝘆 — 𝗧𝗵𝗲 𝗡𝗲𝘅𝘁 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 AI is no longer confined to data centers or the cloud. It is entering the physical world, where machines can see, hear, move, and react on their own. This new wave, called 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗔𝗜, brings intelligence into motion. It powers #robots, #drones and #humanoids that sense, decide, and act in real time. In short, Physical AI gives machines senses, reflexes, and awareness — a body that works with the brain, where #silicon meets motion and algorithms gain instincts. It’s not just about smart code anymore, It is about intelligence that moves. 𝗧𝗵𝗲 𝗕𝗿𝗮𝗶𝗻 & 𝗕𝗼𝗱𝘆 𝗼𝗳 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗔𝗜 𝟭. 𝗛𝗮𝗿𝗱𝘄𝗮𝗿𝗲 𝗹𝗮𝘆𝗲𝗿 — 𝘁𝗵𝗲 𝘀𝗲𝗻𝘀𝗲𝘀 𝗮𝗻𝗱 𝗺𝘂𝘀𝗰𝗹𝗲𝘀 • 𝗦𝗲𝗻𝘀𝗼𝗿𝘀: give machines sight, sound, and touch through cameras, microphones, LiDAR, and pressure sensors. • 𝗔𝗰𝘁𝘂𝗮𝘁𝗼𝗿𝘀: motors, gears, and brakes that control smooth, precise motion. • 𝗦𝗺𝗮𝗿𝘁 𝗔𝗜 𝗠𝗘𝗠𝗦: tiny chips near sensors enabling instant response with minimal power. 𝟮. 𝗔𝗜 𝗰𝗼𝗺𝗽𝘂𝘁𝗲 𝗹𝗮𝘆𝗲𝗿 — 𝘁𝗵𝗲 𝗯𝗿𝗮𝗶𝗻 • 𝗔𝗜 𝗰𝗵𝗶𝗽𝘀: GPUs, NPUs, and AI SoCs that handle perception, planning, and control directly at the edge. • 𝗠𝗲𝗺𝗼𝗿𝘆 & 𝗶𝗻𝘁𝗲𝗿𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝘀: advanced memory stacks (HBM, LPDDR, GDDR) and fast links (UCIe, CXL, NOC) that move data quickly between sensors, compute, and memory. 𝟯. 𝗦𝘆𝘀𝘁𝗲𝗺 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 — 𝘁𝗵𝗲 𝗻𝗲𝗿𝘃𝗼𝘂𝘀 𝘀𝘆𝘀𝘁𝗲𝗺 • 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗹𝗮𝘆𝗲𝗿𝘀: coordinate how sensors and actuators communicate. • 𝗘𝗺𝗯𝗼𝗱𝗶𝗲𝗱-𝗔𝗜 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀: combine simulation, reinforcement learning, and digital twins. • 𝗖𝗹𝗼𝘂𝗱 𝘂𝗽𝗱𝗮𝘁𝗲𝘀: share experience, safety data, and coordination across fleets. 𝟰. 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 — 𝘁𝗵𝗲 𝗺𝗶𝗻𝗱 • 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝗹𝘀 𝗳𝗼𝗿 𝗿𝗼𝗯𝗼𝘁𝗶𝗰𝘀: unite vision, language, and motion understanding. • 𝗠𝘂𝗹𝘁𝗶-𝗺𝗼𝗱𝗮𝗹 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴: merge sound, vision, and touch for natural interaction. • 𝗦𝗲𝗹𝗳-𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗴𝗲𝗻𝘁𝘀: keep improving as they move and sense the world. 𝗛𝗼𝘄 𝗡𝗲𝘅𝘁-𝗚𝗲𝗻 𝗖𝗵𝗶𝗽𝘀 𝗣𝗼𝘄𝗲𝗿 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 The future of Physical AI depends on new chips built for the real world, where speed and efficiency both matter. Leaders like NVIDIA, AMD, Intel Corporation, and Qualcomm are shrinking AI into compact, power-aware packages, while startups such as SiMa.ai, Tenstorrent, d-Matrix, BrainChip , Hailo, and EdgeCortix target everything from smart cameras and drones to autonomous robots and vehicles. These #chips use 3D-stacked memory, #chiplet designs, and optimized interconnects to bring intelligence next to the sensors — turning perception into motion almost instantly. Soon, machines will respond as smoothly as living beings, merging awareness and action in a single loop. Murali Chirala Band of Angels Silicon Catalyst Bala Joshi

Facility's New Best Friend 🐕, Now Powered by AI! Last week, I explored the innovative RoboDog PLUTO at IBM’s Innovation Center. This robotic marvel is designed for hazardous environments, from energy sectors to atomic reactors. PLUTO, a Dynamic Sensing Device, adapts daily to changing environments, such as shifting inventory locations in warehouses. This agility allows PLUTO to bring its sophisticated sensor array directly to objects needing inspection, efficiently and cost-effectively. 🏭 Use Cases Across Industries: A Versatile Robot PLUTO is a game-changer for asset-intensive industries where updating old infrastructure can be prohibitive. It acts like a mobile inspection agent, gathering data on facility conditions and performance. This proactive approach, powered by AI, predicts failures and enhances decision-making, significantly reducing downtime and maintenance costs. 🔥 Real-World Applications and Innovations PLUTO's versatility is evident in projects like fire safety and energy management: - Fire Safety: PLUTO checks if fire extinguishers are intact and correctly positioned, generating maintenance tasks for any discrepancies. - Energy Management: It monitors temperatures in critical components like air conditioners and transformers to support preventive maintenance and avoid overheating. Companies around the globe are already harnessing the capabilities of IBM's PLUTO to transform their operations, showcasing the practical applications and benefits of this innovative technology. Chevron: At Chevron, PLUTO is a critical component of their operational strategy. The company uses the robo-dog for: - Robot-based tank inspections: Ensuring safety and efficiency in storage operations. - Sensors and AI for controlling systems: Enhancing automation and precision in monitoring. - Digital twins of refineries: Utilizing predictive planning to optimize refinery operations. - Machine learning: Analyzing rock compositions and optimizing resource extraction, leading to more efficient production processes. Goldbeck: In the construction sector, Goldbeck employs robo-dogs on its sites to improve safety and efficiency. The robots help monitor site conditions, ensuring that construction processes are up to date and secure, minimizing risks and maximizing productivity. 💬 Feel free to share your thoughts or ask questions about PLUTO and its implications for modern industries! #AI #Innovation #IndustrialAutomation #RoboticSolutions #IBMInnovationCenter

𝐖𝐡𝐲 𝐌𝐨𝐛𝐢𝐥𝐞 𝐑𝐨𝐛𝐨𝐭𝐬 𝐀𝐫𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐇𝐨𝐬𝐩𝐢𝐭𝐚𝐥𝐬 🏥🤖 Hospitals face a growing challenge: labor shortages that stretch staff thin while patient needs continue to rise. To tackle this, many healthcare facilities are turning to mobile robots as innovative, cost-effective solutions. Here’s how these versatile machines are stepping up: ✅ Efficient Supply Transport Mobile robots are ensuring essential supplies—like medications, linens, and lab samples—are delivered quickly and accurately across departments, reducing the burden on staff and improving workflow. ✅ Sanitization & Cleaning Hygiene is critical in healthcare. Robots equipped with UV-C light or disinfection capabilities can clean rooms and high-traffic areas efficiently, helping maintain a safe, sterile environment without overloading janitorial teams. ✅ Patient Meal Delivery From the kitchen to the bedside, mobile robots can deliver meals directly to patients, freeing up nurses and support staff to focus on patient care. These robots don’t just fill gaps—they elevate the quality of care and create a safer, more efficient environment for patients and staff alike. As healthcare continues to evolve, mobile robots are proving to be essential partners in addressing labor shortages while delivering the support hospitals need. 🌟

I am thrilled to share my latest research publication, “Introduction to Swarm Robotics and AI-Driven Fleet Management.” This study dives into the growing shift from single, monolithic robots toward collaborative “swarms” of smaller, specialized robots—coordinated by advanced AI and robust fleet management frameworks. In this academic analysis, I explore: - The theoretical foundations and real-world applications of swarm robotics. - Cutting-edge enabling technologies like 5G/6G communications, edge computing, and AI-based coordination strategies. - Ethical, economic, and legal implications of adopting robot swarms at scale, from workforce displacement to international regulatory challenges. - Future innovations that could accelerate or disrupt the deployment of these distributed robotic systems. If you’re interested in how intelligent, cooperative robotics can revolutionize industries such as logistics, healthcare, agriculture, or defense—and the controversies that come along—this paper will offer valuable insights. Let’s connect and continue the discussion on harnessing (and regulating) these emerging technologies responsibly. Feel free to reach out with any questions or thoughts—I’d love to exchange ideas with fellow professionals and researchers committed to driving meaningful innovation in robotics and AI. Dr. Ivan Del Valle Head of Apsley Labs and Global AI & Emerging Technologies Program Director Apsley Business School, London DOW Academic Campus Sebastian Fuller Sabina Bosa Fuller #SwarmRobotics #AI #ArtificialIntelligence #Robotics #FleetManagement #EmergingTech #EdgeComputing #5G #6G