Adaptive Force-Based Control of Dynamic Legged Locomotion over Uneven Terrain
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Abstract (arXiv)
Agile-legged robots have proven to be highly effective in navigating and performing tasks in complex and challenging environments, including disaster zones and industrial settings. However, these applications normally require the capability of carrying heavy loads while maintaining dynamic motion. Therefore, this paper presents a novel methodology for incorporating adaptive control into a force-based control system. Recent advancements in the control of quadruped robots show that force control can effectively realize dynamic locomotion over rough terrain. By integrating adaptive control into the force-based controller, our proposed approach can maintain the advantages of the baseline framework while adapting to significant model uncertainties and unknown terrain impact models. Experimental validation was successfully conducted on the Unitree A1 robot. With our approach, the robot can carry heavy loads (up to 50% of its weight) while performing dynamic gaits such as fast trotting and bounding across uneven terrains.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Jul 2023.
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Citing papers per year: 2025: 3.
3 papers.
- 2025GentleHumanoid: Learning Upper-body Compliance for Contact-rich Human and Object Interactioncited by 5
- 2025SATA: Safe and Adaptive Torque-Based Locomotion Policies Inspired by Animal Learningcited by 0
- 2025Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robotscited by 0
- 2025GentleHumanoid: Learning Upper-body Compliance for Contact-rich Human and Object Interaction6 Nov 2025
- 2025Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robots4 Aug 2025
- 2025SATA: Safe and Adaptive Torque-Based Locomotion Policies Inspired by Animal Learning18 Feb 2025