Stamatopoulou, Maria;
Tan, Daniel;
Bendikas, Rokas;
Modugno, Valerio;
Li, Zhibin;
Kanoulas, Dimitrios;
(2025)
eGAIT: Multi-Skilled Policy for Energy-efficient Gait Transitions.
IEEE Transactions on Automation Science and Engineering
(In press).
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Abstract
Achieving adaptive, multi-skilled, and energyefficient locomotion is vital for advancing the operation of autonomous quadrupedal systems. This study presents eGAIT, a unified multi-skilled policy enabling energy-efficient and stable gait transitions across nine non-monotonic, velocity-optimized gaits, in response to dynamic velocity commands. The framework leverages a hybrid control architecture that integrates modelbased and learning-based methods to address the entire locomotion pipeline. An MPC-based gait generator produces velocityoptimized trajectories, which are imitated through Proximal Policy Optimization (PPO), driven by a Adversarial Motion Prior (AMP) style reward to train distinct policies for specific velocity ranges. These policies are unified through a Hierarchical Reinforcement Learning (HRL) framework featuring a novel modified Deep Q-Network (eDQN) for real-time velocity-to-policy mapping. Training efficiency is enhanced by an auxiliary selector layer that guides velocity-policy mapping, while a sparsely activated stability reward mechanism ensures smooth gait transitions by incorporating geometric and rotational stability. Extensively validated in simulation and on a Unitree Go1 robot, eGAIT achieves a 100% success rate in velocity-to-policy mapping, a 35% improvement in energy efficiency, a 31% improvement in both velocity tracking and stability compared to the next best state-of-the-art method. This work advances autonomous quadrupedal locomotion, enabling longer, more efficient, and stable operations in dynamic environments. Supplementary materials and visualizations related to the paper can be found at: https://github.com/RPL-CS-UCL/egait/.
| Type: | Article |
|---|---|
| Title: | eGAIT: Multi-Skilled Policy for Energy-efficient Gait Transitions |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Energy-efficient Locomotion, Dynamic Gait Transitions, Multi-skilled Policy, Quadrupedal Locomotion |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10217600 |
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