Adaptive motion planning for legged robots in unstructured terrain using deep reinforcement learning
Legged robots are ideal for navigating unstructured terrain. Unlike wheeled robot platforms, legged robots maintain mobility over rocks, slopes, and uneven surfaces. However, motion planning in such ...
Reinforcement learning (RL) for robotics is often associated with large GPU clusters, distributed infrastructure, and x86-based development environments. Training a humanoid robot with high-fidelity ...
Deep reinforcement learning has exhibited exceptional capabilities in a variety of sequential decision-making problems, providing a standardized learning paradigm for the development of intelligent ...
A humanoid robot weaving through football drills and flawlessly executing one of the sport’s most difficult trick kicks has ...
Forbes contributors publish independent expert analyses and insights. Author, Researcher and Speaker on Technology and Business Innovation. Apr 19, 2025, 03:24am EDT Apr 21, 2025, 10:40am EDT ...
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Hyundai unveils Atlas' soccer learning process
Hyundai Motor Group has unveiled the process by which its subsidiary Boston Dynamics’ humanoid robot ‘Atlas’ learned soccer movements. The group explained that it advanced Atlas’ "full-body control" ...
Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
Marc Raibert, the founder of Boston Dynamics, gave the world a menagerie of two- and four-legged machines capable of jaw-dropping parkour, infectious dance routines, and industrious shelf stacking.
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