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Cascaded Compositional Residual Learning for Complex Interactive Behaviors
K. Niranjan Kumar, Irfan Essa, Sehoon Ha
Real-world autonomous missions often require rich interaction with nearby objects, such as doors or switches, along with effective navigation. However, such complex behaviors are d…
ViNL: Visual Navigation and Locomotion Over Obstacles
Simar Kareer, Naoki Yokoyama, Dhruv Batra +2
We present Visual Navigation and Locomotion over obstacles (ViNL), which enables a quadrupedal robot to navigate unseen apartments while stepping over small obstacles that lie in i…
Unified State Representation Learning under Data Augmentation
Taylor Hearn, Sravan Jayanthi, Sehoon Ha
The capacity for rapid domain adaptation is important to increasing the applicability of reinforcement learning (RL) to real world problems. Generalization of RL agents is critical…
Human Motion Control of Quadrupedal Robots using Deep Reinforcement Learning
Sunwoo Kim, Maks Sorokin, Jehee Lee +1
A motion-based control interface promises flexible robot operations in dangerous environments by combining user intuitions with the robot's motor capabilities. However, designing a…
Safe Reinforcement Learning for Legged Locomotion
Tsung-Yen Yang, Tingnan Zhang, Linda Luu +3
Designing control policies for legged locomotion is complex due to the under-actuated and non-continuous robot dynamics. Model-free reinforcement learning provides promising tools…