Interesting Engineering on MSN
AI-trained quadruped robot walks rough, low-friction terrain without human input
This multi-objective setup encourages natural walking behavior rather than rigid or inefficient movement. A four-stage ...
FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
Deepreinforcement learning has disadvantages such as low sample utilization and slow convergence, and thousandsof trial-and-error iterations are required to perform ...
A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater ...
What if robots could learn to adapt to their surroundings as effortlessly as humans do? The rise of quadruped robots, like Boston Dynamics’ Spot, is turning this vision into reality. By integrating ...
Interesting Engineering on MSN
Video: China’s humanoid robot masters complex skills in hours without prior setup
Last year, PNDbotics debuted its latest humanoid platforms at WAIC 2025, highlighting advances in actuation, control, and ...
TL;DR: FigureAI has developed an AI-powered walking controller for its Figure 02 humanoid robot, enhancing its movement to be more human-like with features such as heel strikes and synchronized arm ...
Trends such as industry-specific AI and a new data economy will affect physical AI in 2026, says a Universal Robots executive ...
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