Trajectory tracking and jumping control of quadruped via phase-aware iLQR controller

Shuomo Zhang , Wei Zou , Hu Su , Chi Zhang , Hongxuan Ma

Biomimetic Intelligence and Robotics ›› 2026, Vol. 6 ›› Issue (1) : 100284

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Biomimetic Intelligence and Robotics ›› 2026, Vol. 6 ›› Issue (1) :100284 DOI: 10.1016/j.birob.2026.100284
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Trajectory tracking and jumping control of quadruped via phase-aware iLQR controller
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Abstract

Jumping is a critical capability for quadruped robots, especially for navigating obstacles and gaps in complex environments. For successful jump, accurate trajectory tracking and robust feedback mechanism are essential, as cumulative deviations from the desired jumping trajectory can lead to instability or landing failure. Existing controllers often rely on fixed joint-level PD control or simplified inverse dynamics, which often fall short in tracking accuracy and robustness. In this paper, we propose a phase-aware iterative Linear Quadratic Regulator (iLQR) framework tailored for dynamic quadruped jumping tasks. By segmenting the jumping motion into distinct phases, we define phase-wise optimal control problem that respects the unique characteristics and requirements of each stage. Moreover, by leveraging a planar full-body dynamics of quadruped in each iLQR sub-problem, we derive a tracking controller consisting time-varying, full-state feedback gains, which shows better performance in tracking accuracy and disturbances rejection over traditional baseline controllers. Extensive simulation and hardware experiments on the Deeprobotics Lite3 quadruped validate the effectiveness and reliability of our proposed method in a number of dynamic jumping scenarios.

Keywords

Quadruped robot / iLQR / Trajectory tracking / Jumping control

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Shuomo Zhang, Wei Zou, Hu Su, Chi Zhang, Hongxuan Ma. Trajectory tracking and jumping control of quadruped via phase-aware iLQR controller. Biomimetic Intelligence and Robotics, 2026, 6(1): 100284 DOI:10.1016/j.birob.2026.100284

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CRediT authorship contribution statement

Shuomo Zhang: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation. Wei Zou: Validation, Supervision. Hu Su: Validation. Chi Zhang: Funding acquisition. Hongxuan Ma: Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work is supported by the Open Projects Program of the State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS2024112), and the Excellent Youth Program of the same laboratory. The authors sincerely appreciate the support from DeepRobotics for providing technical assistance and resources throughout this project.

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