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 ...

A new machine-learning technique can train and control a reconfigurable soft robot that can dynamically change its shape to complete a task. The researchers also built a simulator that can evaluate ...

Last year, PNDbotics debuted its latest humanoid platforms at WAIC 2025, highlighting advances in actuation, control, and ...

Someone looking to book a vacation online today might have very different preferences than they did before the COVID-19 pandemic. Instead of flying to an exotic beach, they might feel more comfortable ...