2 citations · 3 across the 5 of their papers we have counts for
5 papers
Online Time-Informed Kinodynamic Motion Planning of Nonlinear Systems
Fei Meng, Jianbang Liu, Haojie Shi +3
Sampling-based kinodynamic motion planners (SKMPs) are powerful in finding collision-free trajectories for high-dimensional systems under differential constraints. Time-informed se…
An Efficient Model-Based Approach on Learning Agile Motor Skills without Reinforcement
Haojie Shi, Tingguang Li, Qingxu Zhu +3
Learning-based methods have improved locomotion skills of quadruped robots through deep reinforcement learning. However, the sim-to-real gap and low sample efficiency still limit t…
Terrain-Aware Quadrupedal Locomotion via Reinforcement Learning
Haojie Shi, Qingxu Zhu, Lei Han +3
In nature, legged animals have developed the ability to adapt to challenging terrains through perception, allowing them to plan safe body and foot trajectories in advance, which le…
Deep Koopman Operator with Control for Nonlinear Systems
Haojie Shi, Max Q. -H. Meng
Recently Koopman operator has become a promising data-driven tool to facilitate real-time control for unknown nonlinear systems. It maps nonlinear systems into equivalent linear sy…
Reinforcement Learning with Evolutionary Trajectory Generator: A General Approach for Quadrupedal Locomotion
Haojie Shi, Bo Zhou, Hongsheng Zeng +6
Recently reinforcement learning (RL) has emerged as a promising approach for quadrupedal locomotion, which can save the manual effort in conventional approaches such as designing s…