TransCurriculum: Multi-Dimensional Curriculum Learning for Fast & Stable Locomotion
Prakhar Mishra, Amir Hossain Raj, Xuesu Xiao, and Dinesh Manocha

TL;DR
This paper introduces TransCurriculum, a transformer-based multi-dimensional curriculum learning method that enhances high-speed quadrupedal locomotion stability and transferability across diverse terrains and domain parameters.
Contribution
It proposes a novel multi-dimensional curriculum approach that adapts to multiple axes using a transformer-based teacher to improve locomotion performance and transferability.
Findings
Achieves 6.3 m/s maximum velocity in simulation.
Outperforms prior curriculum methods by 18.8% on carpet terrains.
Reduces transfer loss from 27% to 18%.
Abstract
High-speed legged locomotion struggles with stability and transfer losses at higher command velocities during deployment. One reason is that most curricula vary difficulty along single axis, for example increase the range of command velocities, terrain difficulty, or domain parameters (e.g. friction or payload mass) using either fixed update rule or instantaneous rewards while ignoring how the history of robot training has evolved. We propose TransCurriculum, a transformer-based multi-dimensional curriculum learning approach for agile quadrupedal locomotion. TransCurriculum adapts to 3 axes, velocity command targets, terrain difficulty, and domain randomization parameters (friction and payload mass). Rather than feeding task reward history directly into the low-level control policy, our formulation exploits it at the curriculum level. A transformer-based teacher retrieves the sequence…
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Taxonomy
TopicsRobotic Locomotion and Control · Prosthetics and Rehabilitation Robotics · Robot Manipulation and Learning
