Autonomous Robotics for Advanced Applications

Happy to share our latest paper, "Enabling Novel Mission Operations and Interactions with ROSA: The Robot Operating System Agent". This work was led by Rob R. in collaboration with Marcel Kaufmann, Jonathan Becktor, Sangwoo Moon, Kalind Carpenter, Kai Pak, Amanda Towler, Rohan Thakker and myself. Please find the #OpenSource code, paper, and video demonstration linked below. Operating autonomous robots in the field is often challenging, especially at scale and without the proper support of Subject Matter Experts (SMEs). Traditionally, robotic operations require a team of specialists to monitor diagnostics and troubleshoot specific modules. This dependency can become a bottleneck when an SME is unavailable, making it difficult for operators to not only understand the system's functional state but to leverage its full capability set. The challenge grows when scaling to 1-to-N operator-to-robot interactions, particularly with a heterogeneous robot fleet (e.g., walking, roving, flying robots). To address this, we present the ROSA framework, which can leverage state-of-the-art Vision Language Models (VLMs), both on-device and online, to present the autonomy framework's capabilities to operators in an intuitive and accessible way. By enabling a natural language interface, ROSA helps bridge the gap for operators who are not roboticists, such as geologists or first responders, to effectively interact with robots in real-world missions. In our video, we demonstrate ROSA using the NeBula Autonomy framework developed at NASA Jet Propulsion Laboratory to operate in JPL's #MarsYard. Our paper also showcases ROSA's integration with JPL's EELS (Exobiology Extant Life Surveyor) robot and the NVIDIA Carter robot in the IsaacSim environment (stay tuned for ROSA IssacSim extension updates!). These examples highlight ROSA's ability to facilitate interactions across diverse robotic platforms and autonomy frameworks. Paper: https://lnkd.in/g4PRjF4V Github: https://lnkd.in/gwWXmmjR Video: https://lnkd.in/gxKcum27 #Robotics #Autonomy #AI #ROS #FieldRobotics #RobotOperations #NaturalLanguageProcessing #LLM #VLM

Researchers at EPFL have unveiled an innovative robot bird that blends terrestrial and aerial locomotion through advanced physics and engineering principles. Inspired by the biomechanics of avian species, it features lightweight, robust materials and multifunctional legs that store and release energy efficiently, enabling powerful jumps for rapid takeoffs. These legs are modeled to mimic the spring-like motion of tendons and muscles, leveraging principles of elastic potential energy to convert stored energy into kinetic energy during liftoff. This allows for faster, more energy-efficient flight initiation compared to traditional propeller-driven systems, which rely on continuous motor operation to achieve lift. The robot also integrates advanced aerodynamics for stable flight, utilizing biomimetic wing designs that optimize lift-to-drag ratios. Its ability to walk and hop over obstacles stems from precision actuators and sensors that calculate optimal force and trajectory, ensuring smooth transitions between ground and air mobility. These features make it highly adaptive to complex terrains, from rocky landscapes to dense forests, where conventional drones and robots would struggle. Future prospects for this #technology are promising. Its multi-modal capabilities could be applied in search-and-rescue missions, where navigating through collapsed structures or dense vegetation requires both ground movement and aerial maneuverability. In planetary exploration, it could traverse rugged terrains on Mars or the Moon, combining the efficiency of walking with the flexibility of flight. Further advancements may include incorporating solar-powered systems for extended autonomy, swarm robotics for collaborative tasks, and machine learning algorithms to enhance decision-making and obstacle avoidance. This groundbreaking #design not only bridges the gap between terrestrial and aerial robotics but also sets the stage for a new era of versatile, energy-efficient robotic systems capable of tackling a wide range of environmental and industrial challenges. 🎥@EPFL Video rights are reserved for the respective owner. #innovation #whatinspiresme

Robots are leaving the lab. In our Tech Trends 2026 report, I was privilege to be one of the co-authors of the Physical AI chapter (with Jim Rowan, Tim Gaus)—looking at how vision‑language‑action models, onboard NPUs, and modern robotics are pushing autonomous systems from pilots into production. What’s changing: • Physical AI turns robots into adaptive machines that perceive, reason, and act in real time—far beyond preprogrammed automation.  • Onboard compute allows split‑second decisions without cloud dependency, which is critical for safety‑critical environments.  • Economics are improving fast: component commoditization and advanced manufacturing are bringing reliability and scale. Where it’s real: • Amazon’s millionth robot—coordinated by DeepFleet AI—improved fleet travel efficiency ~10%.  • BMW plants have vehicles driving themselves through testing and finishing routes.  • Waymo has passed 10 million paid robotaxi rides; Aurora is hauling freight driverlessly between Dallas and Houston.  • Cities are using AI‑powered drones for bridge inspections; Detroit launched an accessible autonomous shuttle service. Humanoids on the horizon: UBS estimates ~2 million humanoids in workplaces by 2035 and a US$30–50B TAM—driven first by logistics and health care use cases, then consumer scenarios as cost curves fall. What still needs work: Sim‑to‑real training gaps, comprehensive safety governance, cybersecurity for connected fleets, and orchestration across heterogeneous robots. The next 18–24 months will be defined by organizations that tackle these fundamentals. https://lnkd.in/esiAtMN6 Firms like Agility Robotics • Apptronik • Figure • Sanctuary AI • 1X • Cobot • Tesla Optimus • Boston Dynamics • Diligent Robotics • NVIDIA are paving the way to the future. #PhysicalAI #Robotics #Humanoids #Logistics #Manufacturing #Healthcare #SmartCities

Robotics and Physical AI are moving our industry beyond deterministic automation toward adaptive, physics-aware, self-optimizing production systems. A new ASME framework on Physical Artificial Intelligence for Engineering Systems formalizes the stack for this including multimodal perception, physics-grounded world models, learning-based control, simulation-to-reality transfer, and cloud–edge autonomy for real industrial environments. By integrating this stack into next-generation automation we can achieve: • Embodied AI for manipulation, dexterity, compliant control, logistics, assembly • Robotics foundation models for perception, task planning, motion generation, grasp synthesis • High-fidelity digital twins + real-time MPC + model-based RL for closed-loop optimization • Industrial Edge + deterministic control for latency-critical robotic autonomy • Safe HRC with runtime monitoring, verification, and safety-certified architectures • Autonomous, polyfunctional robotic cells capable of reconfiguration, self-calibration, and rapid changeover https://lnkd.in/ghTqd7G2 #PhysicalAI #EmbodiedAI #Robotics #IndustrialRobotics #AutonomousRobots #PolyfunctionalRobots #RobotLearning #ReinforcementLearning #FoundationModels #RoboticsFoundationModels #MultimodalPerception #3DVision #SceneUnderstanding #MotionPlanning #TrajectoryOptimization #ModelPredictiveControl #MPC #DigitalTwin #IndustrialDigitalTwin #CyberPhysicalSystems #CPS #Sim2Real #SimulationToReality #IndustrialEdge #EdgeComputing #DistributedControl #RealTimeControl #AdaptiveAutomation #FlexibleManufacturing #HighMixLowVolume #HRC #HumanRobotCollaboration #SafetyEngineering #FunctionalSafety #Verification #RuntimeMonitoring #GenerativeDesign #AutonomousMachining #PrecisionAssembly #SelfCalibration #ZeroTouchDeployment #IndustrialMetaverse #StochasticAutomation #ResilienceEngineering #Industry4_0 #Industry5_0 #SmartFactory #FutureOfManufacturing #Siemens

DARPA Redefines Space Construction with Autonomous Robots Space exploration is about to get a major upgrade. The Defense Advanced Research Projects Agency (DARPA) is gearing up to test orbital construction through its Novel Orbital Moon Manufacturing, Materials, and Mass-efficient Design (NOM4D) program, launched in 2022. Forget bulky, pre-built components constrained by rocket size—DARPA’s goal is to assemble large, lightweight structures directly in space. Now, in early 2025, NOM4D’s third phase is moving from labs to orbit, with demonstrations slated for 2026 spotlighting a revolutionary technology: autonomous robotic assembly. Orbital Tests Take Shape Two university teams are leading the charge. The California Institute of Technology (Caltech) will send a free-flying robot aboard a Momentus Vigoride vehicle, launched via SpaceX Falcon 9, to autonomously build a 1.4-meter truss in low-Earth orbit. Meanwhile, the University of Illinois Urbana-Champaign (UIUC) will test frontal polymerization—a method to harden composites in space without heavy equipment—aboard the International Space Station. These experiments aim to show that massive structures like antennas, solar arrays, or refueling stations can be crafted efficiently beyond Earth, unshackling design from launch limitations. How Autonomous Robotic Assembly Works Caltech’s test hinges on autonomous robotic assembly: robots building complex frameworks without human oversight. Imagine a robotic system with arms and sensors, floating in microgravity, guided by onboard intelligence. It scans its surroundings with cameras or lasers, plans each move with precision, and uses mechanical arms to connect parts—often within razor-thin tolerances. If a piece shifts mid-process, the robot adapts instantly. In orbit, this could mean turning compact materials into a sturdy truss, all hundreds of miles above Earth, no Earthside controller required. Why It’s a Game-Changer Rockets can’t haul giant structures, but they can carry raw materials. Autonomous assembly is like shipping IKEA flat-packs instead of a fully built desk—only the desk builds itself. This unlocks possibilities like sprawling solar panels for satellites, deep-space antennas, or orbital fuel depots, all constructed where they’re needed. For DARPA, it’s a strategic edge; for commercial space, it’s a blueprint for lunar bases or asteroid mining hubs. Faster, cheaper, and more adaptable, this tech could redefine space infrastructure. Looking to the Stars As February 24, 2025, ticks closer to these 2026 trials, anticipation builds. Caltech’s truss and UIUC’s material tests are small steps with big potential—proofs of concept that could scale up dramatically. If NOM4D succeeds, DARPA may not just transform how we build in space but where we dream humanity’s future lies: out there, with robots paving the way. https://lnkd.in/eZwet6Va UI Urbana-Champaign

Poland Unveils a Fully Autonomous, AI-Driven Warehouse Robot Powered by AMD Introduction: A New Milestone in Industrial Autonomy Robotec.ai, a Polish robotics innovator, is preparing to showcase what it calls the first fully autonomous warehouse robot powered exclusively by AMD Ryzen AI processors. Unlike traditional scripted warehouse automation, this platform uses agentic AI to perceive, reason, plan, and act in real time, moving industrial robotics closer to true self-direction. Breakthrough Capabilities Enabled by AMD and Liquid AI • The robot integrates AMD Ryzen AI processors as its sole compute engine, running both the AI stack and robotics software in parallel with high efficiency. • Liquid AI’s next-generation LFM2-VL Vision Language Models give the system multimodal intelligence, blending perception, reasoning, and natural language understanding. • The robot carries out long-horizon tasks by interpreting spoken or written commands, adapting workflows through autonomous replanning, and operating safely amid mixed warehouse traffic. • It can detect hazards such as spills or blocked exits and take corrective actions without human intervention. Simulation-Driven Development and Embedded Autonomy • Extensive simulation using the Open 3D Engine enables low-risk testing, validation, and refinement of agentic AI behaviors before deployment. • Robotec.ai used synthetic, simulation-derived datasets to fine-tune Liquid AI’s models for domain-specific accuracy and robustness. • LFM2-VL runs entirely on-device, eliminating cloud dependence and reducing latency, a critical requirement for safe, real-time industrial autonomy. • The company plans to migrate from Ryzen processors to AMD’s embedded x86 line as it moves toward commercial deployment. Expanding the Frontier of Reasoning Robots • The robot performs warehouse tasks, serves as an autonomous inspection agent, and alerts operators when unexpected events occur. • AMD’s compute platform delivers high throughput, low latency, and strong power efficiency—key metrics for sustained autonomous operation. • Robotec.ai believes this collaboration demonstrates the next wave of physical intelligence: mobile manipulators powered by agentic AI, capable of high-value, real-world performance. Conclusion: A Step Toward Self-Managing Industrial Environments This demonstration marks an important evolution in warehouse automation. By merging advanced embedded AI, real-time multimodal reasoning, and efficient on-device computation, Robotec.ai shows how autonomous systems can move from repetitive scripts to true environmental understanding. The collaboration with AMD and Liquid AI positions Poland at the forefront of next-generation industrial robotics and signals a broader shift toward intelligent, fully autonomous warehouse ecosystems. I share daily insights with 33,000+ followers across defense, tech, and policy. Keith King https://lnkd.in/gHPvUttw

What if robots could handle heavy logistics over rough terrain, without tracks or human help? [⚡Join 2300+ Robotics enthusiasts - https://lnkd.in/dYxB9iCh] A paper by Marco Arnold, Lukas Hildebrandt, Kaspar Janssen, Efe Ongan, Pascal Bürge, Ádám Gyula Gábriel, James Kennedy, Rishi Lolla, Quanisha Oppliger, Micha Schaaf, Joseph Church, Michael Fritsche, Victor Klemm, Turcan Tuna, Giorgio Valsecchi, Cedric Weibel, Michael Wüthrich, and Marco Hutter Introduces LEVA: a high-payload, high-mobility robot for autonomous logistics across varied terrains. "LEVA: A high-mobility logistic vehicle with legged suspension" • Integrates a legged suspension system using parallel kinematics for enhanced mobility • Traverses stairs and uneven terrain using a reinforcement learning controller • Features steerable wheels and a specialised box pickup mechanism for autonomous payload handling • Transports up to 85 kg across uneven surfaces, steps, and inclines • Achieves a cost of transport as low as 0.15 • Demonstrates off-road capabilities and reliable payload transport through extensive experimental validation LEVA combines the adaptability of legged locomotion with the efficiency of wheeled systems. It addresses the challenge of autonomous material transportation over challenging terrains with significant economic implications. If robots can autonomously handle logistics in unstructured environments, what new applications could this unlock? Paper: https://lnkd.in/gapBPZmr Video - https://lnkd.in/gbE7HNYH #Robotics #AutonomousVehicles #Logistics #ReinforcementLearning #ICRA2025

BREAKING NEWS: 🇯🇵 Japan Successfully Tests Space Robots That Assemble Structures in Orbit Japan has successfully tested autonomous space robots capable of assembling large structures directly in orbit. Instead of launching fully built spacecraft, these robots piece together components in space with millimeter precision. The robots use AI-driven coordination to adapt to microgravity and unexpected motion. During testing, they successfully assembled modular structures while correcting alignment errors in real time. This could dramatically reduce launch costs and enable the construction of massive space telescopes, habitats, and power stations. Engineers say this technology is essential for long-term human activity beyond Earth. It marks a major step toward sustainable space infrastructure.

This video showcases the application of an automated manipulation system in industrial processes, where robots perform the transportation and positioning of steel plates into mechanical presses responsible for shaping the parts. Automating this procedure is essential in advanced manufacturing, enabling greater operational precision, process repeatability, and optimization of production cycles. Moreover, replacing manual operations with robotic systems eliminates occupational hazards associated with handling heavy materials and high-pressure equipment, ensuring a safer and ergonomically optimized work environment. The implementation of robotic systems contributes to quality standardization, reduces process variability, and enhances production efficiency, aligning with Industry 4.0 principles and best practices in production engineering. #KUKA #FANUC #SCHULER #PROCESS #SIMULATION