Page 8: Research news on Autonomous robotic locomotion

Autonomous robotic locomotion investigates how robots perceive, plan, and execute movement in complex, often unstructured environments with minimal human intervention. Work in this area spans legged, wheeled, aerial, amphibious, and soft robots, emphasizing bio-inspired control strategies, neuromechanics, and learning-based methods for gait adaptation, trajectory modulation, and slip prevention. Research also addresses navigation and mapping, kinematic and impedance control, and human–robot collaboration, enabling robots to perform tasks such as construction, waste collection, manipulation, and agile behaviors like parkour, badminton, and swarm-based assembly.

Robotics

A common language to describe and assess human–agent teams

Understanding how humans and AI or robotic agents can work together effectively requires a shared foundation for experimentation. A University of Michigan-led team developed a new taxonomy to serve as a common language among ...

Engineering

AI bots could match scientist-level design problem solving

Engineers at Duke University have constructed a group of AI bots that together can solve complex design problems nearly as well as a fully trained scientist. The results, the researchers say, show how AI might soon automate ...

Robotics

AI trained robots, drones, team up with emergency rescue

In a simulated natural disaster, robotic drones from the University of Maryland's RoboScout Team arrived first, scanning the area for survivors. They beamed patients' locations to robot dogs and medics on the ground to quickly ...

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