Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllers
Legged locomotion has recently achieved remarkable success with the progress of machine
learning techniques, especially deep reinforcement learning (RL). Controllers employing …
learning techniques, especially deep reinforcement learning (RL). Controllers employing …
Orchestrating Method Ensembles to Adapt to Resource Requirements and Constraints during Robotic Task Execution
FS Lay, A Dömel, NY Lii, F Stulp - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Robot behavior designers commonly select one method–eg A* or RRT–that is assumed to
have the appropriate trade-off for a given domain between computational load, computation …
have the appropriate trade-off for a given domain between computational load, computation …
Robust Locomotion Policy with Adaptive Lipschitz Constraint for Legged Robots
Deep Reinforcement Learning (DRL) has achieved significant advancements in legged
robot locomotion tasks. However, neural network-based control policies suffer from action …
robot locomotion tasks. However, neural network-based control policies suffer from action …
Automatic Tracking Control Strategy of Autonomous Trains Considering Speed Restrictions: Using the Improved Offline Deep Reinforcement Learning Method
W Liu, Q Feng, S Xiao, H Li - IEEE Access, 2024 - ieeexplore.ieee.org
Previous research on automatic control of high-speed trains in speed limit sections is
insufficient. This article proposes a new offline reinforcement learning strategy for automatic …
insufficient. This article proposes a new offline reinforcement learning strategy for automatic …
Bridging the Reality Gap: Analyzing Sim-to-Real Transfer Techniques for Reinforcement Learning in Humanoid Bipedal Locomotion
Reinforcement learning (RL) offers a promising solution for controlling humanoid robots,
particularly for bipedal locomotion, by learning adaptive and flexible control strategies …
particularly for bipedal locomotion, by learning adaptive and flexible control strategies …