🤖 Boots on. Clipboard optional. Tilbury Douglas says it has become the first tier one contractor to deploy a humanoid robot on a live construction site. The robot, named Douglas, is being used for admin and data-collection tasks, including autonomous site navigation, 360° imagery capture, and progress reporting to support health and safety monitoring. Construction’s digital shift just got a very literal pair of legs. https://bit.ly/4cznh7H #Construction #ConTech #Innovation #Robotics #HealthAndSafety #DigitalConstruction

What does real progress toward autonomous warehouse robotics actually look like? A humanoid robot that can independently scan, navigate, and position itself while a human steps in only where precision still matters most. This system is already live in a customer warehouse. In this workflow: → The robot handles navigation end-to-end → The operator takes over for the pick and placement → Control shifts seamlessly between autonomy and teleoperation This is how yondu scales today and moves toward full autonomy with every task completed.

In trajectory tracking control, we typically assume the desired trajectory is twice differentiable, since the controller directly uses the second derivative. But is this really necessary? A recent article shows that controllers can be designed to track non‑differentiable trajectories (with kinks or corners) - something not possible with standard approaches. This could significantly broaden what we can do in robotics and autonomous systems. Curious to hear your thoughts: 👉 Where do you see the biggest opportunities for controllers that can handle non-smooth trajectories? #ControlSystems #Robotics #NonlinearControl #Research #TrajectoryTracking #Autonomy https://lnkd.in/gSZyhMXh

Formation control is easy to describe and hard to implement when vehicles were never designed for it. Humans learn wedge, file, and staggered column through repetition, spacing, and shared context. Most autonomous platforms do not have that behavior natively. So the problem becomes how to create formation behavior indirectly through synchronized movement, local sensing, and shared world understanding. One path is sensor-driven. Each vehicle uses local perception, proximity sensing, and scene awareness to continuously predict where it should move relative to the others. Another path is distributed. Each platform shares part of its local world model with teammates, allowing the group to maintain formation based on both self-observation and team state. That second path is especially important. Formation control is not just geometry. It is communication, orientation, and common reference frames. For defense autonomy, that means the future is not only better path planning. It is shared latent representations that let teams coordinate movement the way humans do, but at machine speed. #DefenseAI #MultiAgentSystems #GroundAutonomy #Robotics

Security is full of manual work nobody notices until it stops. Logs, rounds, checklists, handovers. Autonomous robots take that burden off the team so they can focus on what only humans can do. Quarero Robotics secures sites and assets with autonomous security robots. Autonomous monitoring for indoor and outdoor areas – no capital expenditure, subscription model. 🌐 https://lnkd.in/ePQxygWz 📩 info@quarerorobotics.com

Is the future of factory inspections walking on four legs? 🤖🐕 Manual walk-throughs in hazardous environments are becoming a thing of the past. The real game-changer isn't just the robot itself, it's what the robot can see and hear. Our latest integration features the HERTZINNO HZ-FA-371T mounted on agile quadruped robots (Robot Dogs), creating a fully autonomous, 24/7 inspection powerhouse. Why this matters for Industry 4.0: 🔹 Zero-Risk Monitoring: Send robots into high-voltage or toxic zones while your team stays safe. 🔹 Acoustic + Thermal Intelligence: Detect gas leaks and thermal hotspots simultaneously, even in complete darkness. 🔹 AI-Driven Navigation: The HZ-FA-371T provides the "digital ears" needed to identify anomalies that traditional cameras miss. The era of unmanned, intelligent inspection isn't "coming"—it's already here. [Check the FIRST COMMENT for the full technical breakdown and case study! 👇] #Industry40 #Robotics #AcousticCamera #HertzInno #PredictiveMaintenance #RobotDog #SmartFactory #UnmannedInspection #Innovation #Engineering #Automation

Glad to share a project I recently worked on using ROS2 and TurtleBot3 in simulation. I designed a warehouse environment in Gazebo and implemented a full pipeline including SLAM mapping, autonomous navigation, and multi-point waypoint navigation. The robot was able to localize itself, move to selected goals, and even handle unexpected obstacles in real time. It was a great hands on experience connecting everything together and seeing how these systems actually work in practice. Really glad to be learning this under the supervision of Ts. Suresh Gobee Looking forward to taking this further 🤖 #ROS2 #Robotics #TurtleBot3 #Gazebo #AutonomousSystems

Security shouldn’t depend on who happens to be on shift. Skills, experience and attention vary wildly between individuals. Autonomous systems provide a consistent baseline that every team can rely on. Quarero Robotics secures sites and assets with autonomous security robots. Autonomous monitoring for indoor and outdoor areas – no capital expenditure, subscription model. 🌐 https://lnkd.in/ePQxygWz 📩 info@quarerorobotics.com

𝗧𝗵𝗲 𝗿𝗼𝗯𝗼𝘁 𝗿𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝘀 𝗵𝗲𝗿𝗲. 𝗜𝘁 𝗷𝘂𝘀𝘁 𝗻𝗲𝗲𝗱𝘀 𝘆𝗼𝘂𝗿 𝗵𝗲𝗹𝗽 𝗰𝗿𝗼𝘀𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝘀𝘁𝗿𝗲𝗲𝘁. 𝗦𝗲𝗿𝗶𝗼𝘂𝘀𝗹𝘆. This isn't just a funny clip. It exposes a real crack in the autonomous future we're building. Robots can now navigate city streets on their own. Detect obstacles. Avoid pedestrians. Deliver packages. But they still can't press a crosswalk button. Because crosswalk buttons were built for human hands. Not robot arms. That's the real problem nobody is talking about We're deploying intelligent machines into a world designed entirely for humans. And when they hit a wall? They ask us for help. The bigger question isn't "is this robot smart enough?" It's are our cities, rules, and infrastructure ready for robots at all?

Global, Static, Dynamic Layers for Robotics: A New Environment Model for Autonomous Mobile Robots A highly recommended new preprint addresses outdoor navigation for autonomous mobile robots (AMRs). The authors adapt HD map concepts from autonomous driving for unstructured environments such as sidewalks and urban spaces. The core of this work is a newly developed 3-layer framework: 🌍 Global Layer: Path generation based on Lanelet2. 🗺️ Static Layer: Map generation and collection of pedestrian data (pose, movement, and occupancy). ⚡ Dynamic Layer: Real-time localization and pedestrian-aware navigation. The paper is a collaborative effort by Swaraj Tendulkar, Abhishek Nannuri, Sagar Nagdev, and Frank Schrödel, developed as part of ongoing research at the Chair of Automation Control and Robotics at Hochschule Schmalkalden. The goal of this work is to advance robust robot navigation in shared outdoor spaces. As next steps, the research team is planning practical implementation and field testing – and they look forward to feedback from the community. 📄 Read the preprint here: https://lnkd.in/eeKpbck6 #Robotics #AutonomousMobileRobots #AMR #Navigation #HochschuleSchmalkalden #Research #Preprint #AutonomousSystems