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Jiatao Ding

7 accepted papers

2025

Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning

IROS 2025

Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this challenge via imitation-based deep reinforcement learning with a progressive training process. To start, we learn the jum

Cited by 1SourceScholar
2024

Robust Jumping With an Articulated Soft Quadruped Via Trajectory Optimization and Iterative Learning

RA-L 2024

Quadrupeds deployed in real-world scenarios need to be robust to unmodelled dynamic effects. In this work, we aim to increase the robustness of quadrupedal periodic forward jumping (i.e., pronking) by unifying cutting-edge model-based trajectory optimization and iterative learning control. Using a r

Cited by 16SourceScholar
2024

Two-Stage Learning of Highly Dynamic Motions with Rigid and Articulated Soft Quadrupeds

ICRA 2024poster

Controlled execution of dynamic motions in quadrupedal robots, especially those with articulated soft bodies, presents a unique set of challenges that traditional methods struggle to address efficiently. In this study, we tackle these issues by relying on a simple yet effective two-stage learning fr…

Cited by 9SourcecodeScholar
2021

Versatile Locomotion by Integrating Ankle, Hip, Stepping, and Height Variation Strategies

ICRA 2021poster

Stable walking in real-world environments is a challenging task for humanoid robots, especially when considering the dynamic disturbances, e.g., caused by external perturbations that may be encountered during locomotion. The varying nature of disturbance necessitates high adaptability. In this paper…

Cited by 9SourceScholar
2020

Robust Gait Synthesis Combining Constrained Optimization and Imitation Learning

IROS 2020poster

Despite plenty of motion planning strategies have been proposed for bipedal locomotion, enhancing the walking robustness in real-world environments is still an open question. This paper focuses on robust body and leg trajectories synthesis through integrating constrained optimization with imitation…

Cited by 10SourceScholar
2019

Versatile Reactive Bipedal Locomotion Planning Through Hierarchical Optimization

ICRA 2019poster

When experiencing disturbances during locomotion, human beings use several strategies to maintain balance, e.g. changing posture, modulating step frequency and location. However, when it comes to the gait generation for humanoid robots, modifying step time or body posture in real time introduces non…

Cited by 13SourceScholar