Teleoperation of humanoid robots: A survey
Teleoperation of humanoid robots enables the integration of the cognitive skills and domain
expertise of humans with the physical capabilities of humanoid robots. The operational …
expertise of humans with the physical capabilities of humanoid robots. The operational …
Robot learning from randomized simulations: A review
The rise of deep learning has caused a paradigm shift in robotics research, favoring
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
Learning agile soccer skills for a bipedal robot with deep reinforcement learning
We investigated whether deep reinforcement learning (deep RL) is able to synthesize
sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be …
sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be …
Learning robust perceptive locomotion for quadrupedal robots in the wild
Legged robots that can operate autonomously in remote and hazardous environments will
greatly increase opportunities for exploration into underexplored areas. Exteroceptive …
greatly increase opportunities for exploration into underexplored areas. Exteroceptive …
Rapid locomotion via reinforcement learning
Agile maneuvers such as sprinting and high-speed turning in the wild are challenging for
legged robots. We present an end-to-end learned controller that achieves record agility for …
legged robots. We present an end-to-end learned controller that achieves record agility for …
Learning quadrupedal locomotion over challenging terrain
Legged locomotion can extend the operational domain of robots to some of the most
challenging environments on Earth. However, conventional controllers for legged …
challenging environments on Earth. However, conventional controllers for legged …
Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control
This paper presents a comprehensive study on using deep reinforcement learning (RL) to
create dynamic locomotion controllers for bipedal robots. Going beyond focusing on a single …
create dynamic locomotion controllers for bipedal robots. Going beyond focusing on a single …
Learning agile robotic locomotion skills by imitating animals
Multi-expert learning of adaptive legged locomotion
Achieving versatile robot locomotion requires motor skills that can adapt to previously
unseen situations. We propose a multi-expert learning architecture (MELA) that learns to …
unseen situations. We propose a multi-expert learning architecture (MELA) that learns to …