From the 1 of 14 linked papers with an AI index.
5 papers · 1 filter
Accelerating Sampling-Based Control via Learned Linear Koopman Dynamics
Wenjian Hao, Yuxuan Fang, Zehui Lu +1
The paper proposes a model predictive path integral control method that replaces costly nonlinear dynamics with a learned linear deep Koopman operator, enabling faster trajectory s…
Online Intention Prediction via Control-Informed Learning
Tianyu Zhou, Zihao Liang, Zehui Lu +1
This paper presents an online intention prediction framework for estimating the goal state of autonomous systems in real time, even when intention is time-varying, and system dynam…
Trajectory Prediction via Bayesian Intention Inference under Unknown Goals and Kinematics
Shunan Yin, Zehui Lu, Shaoshuai Mou
This work introduces an adaptive Bayesian algorithm for real-time trajectory prediction via intention inference, where a target's intentions and motion characteristics are unknown…
Reward-Based Collision-Free Algorithm for Trajectory Planning of Autonomous Robots
Jose D. Hoyos, Tianyu Zhou, Zehui Lu +1
This paper proposes a novel mission planning algorithm for autonomous robots that selects an optimal waypoint sequence from a predefined set to maximize total reward while satisfyi…
A Differentiable Dynamic Modeling Approach to Integrated Motion Planning and Actuator Physical Design for Mobile Manipulators
Zehui Lu, Yebin Wang
This paper investigates the differentiable dynamic modeling of mobile manipulators to facilitate efficient motion planning and physical design of actuators, where the actuator desi…