Page 6: 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

Closing the gap between animal movement and robotic control

Animals move with a level of precision and adaptability that robots struggle to match. In Carnegie Mellon University's Department of Mechanical Engineering, researchers are developing a new AI-driven approach to uncover how ...

Robotics

For autonomous robots, not all rules are equal

From driving cars to flying drones, as autonomous robots take on more responsibility, they also face more human-like dilemmas—including what to do when rules collide.

Robotics

What will it take to make AI-enabled robots safer?

The effort to "align" AI with human values is falling dangerously short in robotic systems, according to researchers from Penn Engineering, Carnegie Mellon University (CMU) and the University of Oxford. In a new paper appearing ...

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