Asset Details
Do you wish to reserve the book?
Approximate optimal and scalable control for collision-free formation of uncertain nonholonomic robots
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Approximate optimal and scalable control for collision-free formation of uncertain nonholonomic robots
Do you wish to request the book?
Approximate optimal and scalable control for collision-free formation of uncertain nonholonomic robots
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Approximate optimal and scalable control for collision-free formation of uncertain nonholonomic robots
2024
Overview
This paper studies the formation tracking problem for nonholonomic multirobot systems under model uncertainties. A new local variable is designed to transform the collision-free formation control objective into an optimization problem through integrating several filtered signals into tracking errors. The optimal control policies for nominal kinematic model are learned by approximate dynamic programming (ADP) technique using a simplified critic-only neural network (NN) based algorithm, which scales well since the computational complexity is independent with the number of robots and obstacles. Then, to handle the effects from robots’ uncertainties, the ADP control policies are redesigned by adding a two time-scale based compensator. It is shown that under proper conditions, the NN weights’ estimation errors are uniformly ultimately bounded, while the robust formation tracking and collision avoidance can be achieved. Numerical simulations finally illustrate the effectiveness of the proposed controller.
