1 citations · 1 across the 8 of their papers we have counts for
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PPO-EAL: Exact Augmented Lagrangian Proximal Policy Optimization for Safe Robotic Control
Jiatao Ding, Songqun Gao, Andrea Del Prete +1
Reinforcement learning (RL) has emerged as a promising solution to accomplish complex robotic control tasks; however, most of the current work ignores the safety requirements. Safe…
Towards Terrain-Aware Safe Locomotion for Quadrupedal Robots Using Proprioceptive Sensing
Peiyu Yang, Jiatao Ding, Wei Pan +2
Achieving safe quadrupedal locomotion in real-world environments has attracted much attention in recent years. When walking over uneven terrain, achieving reliable estimation and r…
A Task-Driven, Planner-in-the-Loop Computational Design Framework for Modular Manipulators
Maolin Lei, Edoardo Romiti, Arturo Laurenzi +5
Modular manipulators composed of pre-manufactured and interchangeable modules offer high adaptability across diverse tasks. However, their deployment requires generating feasible m…
Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robots
Gioele Buriani, Jingyue Liu, Maximilian Stölzle +2
Reduced-order models are central to motion planning and control of quadruped robots, yet existing templates are often hand-crafted for a specific locomotion modality. This motivate…
Versatile, Robust, and Explosive Locomotion with Rigid and Articulated Compliant Quadrupeds
Jiatao Ding, Peiyu Yang, Fabio Boekel +4
Achieving versatile and explosive motion with robustness against dynamic uncertainties is a challenging task. Introducing parallel compliance in quadrupedal design is deemed to enh…
Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning
Georgios Apostolides, Wei Pan, Jens Kober +2
Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this c…
Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-free Design
Vassil Atanassov, Jiatao Ding, Jens Kober +2
Deep reinforcement learning (DRL) has emerged as a promising solution to mastering explosive and versatile quadrupedal jumping skills. However, current DRL-based frameworks usually…
Two-Stage Learning of Highly Dynamic Motions with Rigid and Articulated Soft Quadrupeds
Francecso Vezzi, Jiatao Ding, Antonin Raffin +2
Controlled execution of dynamic motions in quadrupedal robots, especially those with articulated soft bodies, presents a unique set of challenges that traditional methods struggle…