Design and experimental validation of deep reinforcement learning-based fast trajectory planning and control for mobile robot in unknown environment

R Chai, H Niu, J Carrasco, F Arvin… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article is concerned with the problem of planning optimal maneuver trajectories and
guiding the mobile robot toward target positions in uncertain environments for exploration …

Deep learning-based trajectory planning and control for autonomous ground vehicle parking maneuver

R Chai, D Liu, T Liu, A Tsourdos… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this paper, a novel integrated real-time trajectory planning and tracking control framework
capable of dealing with autonomous ground vehicle (AGV) parking maneuver problems is …

Automatic parking control of unmanned vehicle based on switching control algorithm and backstep**

H Gao, J Zhu, X Li, Y Kang, J Li… - IEEE/ASME Transactions …, 2020 - ieeexplore.ieee.org
This article presents a simple control method for the fully automatic parking of an unmanned
vehicle. This method is based on the switching control algorithm and backstep** theory …

Multiobjective overtaking maneuver planning for autonomous ground vehicles

R Chai, A Tsourdos, A Savvaris, S Chai… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Constrained autonomous vehicle overtaking trajectories are usually difficult to generate due
to certain practical requirements and complex environmental limitations. This problem …

A fast density peak clustering based particle swarm optimizer for dynamic optimization

F Li, Q Yue, Y Liu, H Ouyang, F Gu - Expert Systems with Applications, 2024 - Elsevier
Dynamic optimization problems (DOPs) are optimization problems with time evolution
characteristics. In this type of problem, the decision variables and the state variables change …

An effective memetic algorithm for multi-objective job-shop scheduling

G Gong, Q Deng, R Chiong, X Gong… - Knowledge-Based Systems, 2019 - Elsevier
This paper presents an effective memetic algorithm (EMA) to solve the multi-objective job
shop scheduling problem. A new hybrid crossover operator is designed to enhance the …