Abstract
Although aerial-legged robots offer combined agility and efficiency, controlling high-speed hopping under complex hybrid dynamics is challenging. Reinforcement Learning (RL) is promising but prone to energy-inefficient "reward hacking". We propose a Dynamics-Informed RL framework for a monopedal hopping quadcopter. By embedding a target Specific Energy into the reward, we constrain the optimization to a physically viable energy manifold, ensuring stable hopping behaviour. By rewarding the phase-consistent behavior, it can encourage bio-inspired stance-phase impulse. Furthermore, penalizing the electro-mechanical power waste induces the motors generate an efficient impulse. This enables the policy to inject energy strictly during spring restitution without heuristic state machines. MuJoCo simulations validate robust height regulation and forward velocity tracking up to 2.0 m/s despite severe attitude-contact coupling. Ultimately, our approach yields a highly agile hopping gait, reducing energy consumption by 82% and 73% compared to hovering baselines and inefficiency baseline, respectively.
Keywords
Publication details
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Cite this article
APA 7
Chen, R., Zhang, Q., Zhong, Z., Yun, Z., Or, Y., & Liu, M. (2026). Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter. https://omanscience.com/en/articles/dynamics-informed-reinforcement-learning-for-agile-and-energy-efficient-locomotion-of-a-monopedal-hopping-quadcopter
MLA 9
Chen, Ruigang, et al. "Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter." https://omanscience.com/en/articles/dynamics-informed-reinforcement-learning-for-agile-and-energy-efficient-locomotion-of-a-monopedal-hopping-quadcopter.
Chicago (author–date)
Chen, Ruigang, Qi Zhang, Zhicheng Zhong, Zhuorui Yun, Yizhar Or, and Mingyi Liu. 2026. "Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter." https://omanscience.com/en/articles/dynamics-informed-reinforcement-learning-for-agile-and-energy-efficient-locomotion-of-a-monopedal-hopping-quadcopter.
Harvard
Chen, R., Zhang, Q., Zhong, Z., Yun, Z., Or, Y. and Liu, M. (2026) 'Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter', Available at: https://omanscience.com/en/articles/dynamics-informed-reinforcement-learning-for-agile-and-energy-efficient-locomotion-of-a-monopedal-hopping-quadcopter.
Vancouver
Chen R, Zhang Q, Zhong Z, Yun Z, Or Y, Liu M. Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter. https://omanscience.com/en/articles/dynamics-informed-reinforcement-learning-for-agile-and-energy-efficient-locomotion-of-a-monopedal-hopping-quadcopter
IEEE
R. Chen, Q. Zhang, Z. Zhong, Z. Yun, Y. Or, and M. Liu, "Dynamics-Informed Reinforcement Learning for Agile and Energy-Efficient Locomotion of a Monopedal Hopping Quadcopter," https://omanscience.com/en/articles/dynamics-informed-reinforcement-learning-for-agile-and-energy-efficient-locomotion-of-a-monopedal-hopping-quadcopter.