55 citations · 122 across the 15 of their papers we have counts for
15 papers
Complementarity-Free Multi-Contact Modeling and Optimization for Dexterous Manipulation
Wanxin Jin
A significant barrier preventing model-based methods from achieving real-time and versatile dexterous robotic manipulation is the inherent complexity of multi-contact dynamics. Tra…
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning
Ni Dang, Tao Shi, Zengjie Zhang +3
The driving style of an Autonomous Vehicle (AV) refers to how it behaves and interacts with other AVs. In a multi-vehicle autonomous driving system, an AV capable of identifying th…
Task-Driven Hybrid Model Reduction for Dexterous Manipulation
Wanxin Jin, Michael Posa
In contact-rich tasks, like dexterous manipulation, the hybrid nature of making and breaking contact creates challenges for model representation and control. For example, choosing…
Cooperative Tuning of Multi-Agent Optimal Control Systems
Zehui Lu, Wanxin Jin, Shaoshuai Mou +1
This paper investigates the problem of cooperative tuning of multi-agent optimal control systems, where a network of agents (i.e. multiple coupled optimal control systems) adjusts…
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao +6
It is quite challenging to ensure the safety of reinforcement learning (RL) agents in an unknown and stochastic environment under hard constraints that require the system state not…
Distributed Differentiable Dynamic Game for Multi-robot Coordination
Yizhi Zhou, Wanxin Jin, Xuan Wang
This paper develops a Distributed Differentiable Dynamic Game (D3G) framework, which can efficiently solve the forward and inverse problems in multi-robot coordination. We formulat…
Learning Linear Complementarity Systems
Wanxin Jin, Alp Aydinoglu, Mathew Halm +1
This paper investigates the learning, or system identification, of a class of piecewise-affine dynamical systems known as linear complementarity systems (LCSs). We propose a violat…
Inequality Constrained Trajectory Optimization with A Hybrid Multiple-shooting iLQR
Yunxi Tang, Xiangyu Chu, Wanxin Jin +1
Trajectory optimization has been used extensively in robotic systems. In particular, iterative Linear Quadratic Regulator (iLQR) has performed well as an off-line planner and onlin…
Safe Pontryagin Differentiable Programming
Wanxin Jin, Shaoshuai Mou, George J. Pappas
We propose a Safe Pontryagin Differentiable Programming (Safe PDP) methodology, which establishes a theoretical and algorithmic framework to solve a broad class of safety-critical…
Learning from Human Directional Corrections
Wanxin Jin, Todd D. Murphey, Zehui Lu +1
This paper proposes a novel approach that enables a robot to learn an objective function incrementally from human directional corrections. Existing methods learn from human magnitu…
Learning Objective Functions Incrementally by Inverse Optimal Control
Zihao Liang, Wanxin Jin, Shaoshuai Mou
This paper proposes an inverse optimal control method which enables a robot to incrementally learn a control objective function from a collection of trajectory segments. By saying…
Learning from Sparse Demonstrations
Wanxin Jin, Todd D. Murphey, Dana Kulić +2
This paper develops the method of Continuous Pontryagin Differentiable Programming (Continuous PDP), which enables a robot to learn an objective function from a few sparsely demons…
Neural Certificates for Safe Control Policies
Wanxin Jin, Zhaoran Wang, Zhuoran Yang +1
This paper develops an approach to learn a policy of a dynamical system that is guaranteed to be both provably safe and goal-reaching. Here, the safety means that a policy must not…
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
Wanxin Jin, Zhaoran Wang, Zhuoran Yang +1
This paper develops a Pontryagin Differentiable Programming (PDP) methodology, which establishes a unified framework to solve a broad class of learning and control tasks. The PDP d…
Inverse Optimal Control from Incomplete Trajectory Observations
Wanxin Jin, Dana Kulić, Shaoshuai Mou +1
This article develops a methodology that enables learning an objective function of an optimal control system from incomplete trajectory observations. The objective function is assu…