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Learning-based legged locomotion: State of the art and future perspectives
S Ha, J Lee, M van de Panne, Z ** control through reinforcement learning
This work aims to push the limits of agility for bipedal robots by enabling a torque-controlled
bipedal robot to perform robust and versatile dynamic jumps in the real world. We present a …
bipedal robot to perform robust and versatile dynamic jumps in the real world. We present a …
Humanoid locomotion and manipulation: Current progress and challenges in control, planning, and learning
Humanoid robots have great potential to perform various human-level skills. These skills
involve locomotion, manipulation, and cognitive capabilities. Driven by advances in machine …
involve locomotion, manipulation, and cognitive capabilities. Driven by advances in machine …
Slomo: A general system for legged robot motion imitation from casual videos
We present SLoMo: a first-of-its-kind framework for transferring skilled motions from casually
captured “in-the-wild” video footage of humans and animals to legged robots. SLoMo works …
captured “in-the-wild” video footage of humans and animals to legged robots. SLoMo works …
Risk-averse trajectory optimization via sample average approximation
Trajectory optimization under uncertainty underpins a wide range of applications in robotics.
However, existing methods are limited in terms of reasoning about sources of epistemic and …
However, existing methods are limited in terms of reasoning about sources of epistemic and …
Integrated task and motion planning for safe legged navigation in partially observable environments
This study proposes a hierarchically integrated framework for safe task and motion planning
(TAMP) of bipedal locomotion in a partially observable environment with dynamic obstacles …
(TAMP) of bipedal locomotion in a partially observable environment with dynamic obstacles …
Model-free reinforcement learning for robust locomotion using demonstrations from trajectory optimization
We present a general, two-stage reinforcement learning approach to create robust policies
that can be deployed on real robots without any additional training using a single …
that can be deployed on real robots without any additional training using a single …
Fall prediction, control, and recovery of quadruped robots
When legged robots perform complex tasks in unstructured environments, falls are
inevitable due to unknown external disturbances. However, current research mainly focuses …
inevitable due to unknown external disturbances. However, current research mainly focuses …
Robust pivoting manipulation using contact implicit bilevel optimization
Generalizable manipulation requires that robots be able to interact with novel objects and
environment. This requirement makes manipulation extremely challenging as a robot has to …
environment. This requirement makes manipulation extremely challenging as a robot has to …