A simulation and experimental study on wheeled mobile robot path control in road roundabout environment

Abstract

A robust control algorithm for tracking a wheeled mobile robot navigating in a pre-planned path while passing through the road's roundabout environment is presented in this article. The proposed control algorithm is derived from both the kinematic and dynamic modelling of a non-holonomic wheeled mobile robot that is driven by a differential drive system. The road's roundabout is represented in a grid map and the path of the mobile robot is determined using a novel approach, the so-called laser simulator technique within the roundabout environment according to the respective road rules. The main control scheme is experimented in both simulation and experimental study using the resolvedacceleration control and active force control strategy to enable the robot to strictly follow the predefined path in the presence of disturbances. A fusion of the resolved-acceleration control-active force control controller with Kalman Filter has been used empirically in real time to control the wheeled mobile robot in the road's roundabout setting with the specific purpose of eliminating the noises. Both the simulation and the experimental results show the capability of the proposed controller to track the robot in the predefined path robustly and cancel the effect of the disturbances.

Energy-Efficient Local Path Planning of a Self-Guided Vehicle by Considering the Load Position

“…Regarding this point, a proper kinetic model is required. However, in the literature, the displacement of CoM has been considered to move just in the longitudinal direction in kinetic models [15], [16]. But in reality, when there is a load on the vehicle's platform, the CoM shifts on both longitudinal and lateral axes according to load properties.…”

A Fusion Method of Local Path Planning for Mobile Robots Based on LSTM Neural Network and Reinforcement Learning

“…e methods may also fail when the robot enters an uncertain environment. Local path planning explores a collision-free optimal path to reach the target point based on environmental information detected by onboard sensors [9,10]. Commonly used local path planning algorithms include potential field method, fuzzy logic, neural network, heuristic algorithm, and various hybrid algorithms [11][12][13].…”

Practical Implementation of Passivity-Based Robust Switching Posture Control of Wheeled Mobile Robots With Model Uncertainty

“…[15] discusses experimental validation for the power consumption of tracked and wheeled small mobile robots on deformable terrain. [16] describes the experimental studies for the navigation and the tracking of the predefined roundabout trajectory of WMR via RAC, AFC, RAC-AFC and, RAC-AFC-KF controllers. It shows that the performance of RAC-AFC-KF controllers is superior to other approaches, which eliminates the delay in processing the data from the sensors and noises.…”

“…This proposed hybrid control strategy focus on reducing the effort required for modeling the complex systems by approximating the unknown dynamics using input and feedback information of past time instances. Although [9][10][11][12][13][14][15][16][17][18] present the experimental studies of WMR for tracking and posture stabilization based on various control approaches, the practical implementation and experimental investigation of robust switching control (designed based on the 2 nd order dynamics for the posture stabilization of WMR) have not been fully explored. Therefore, this work as a sequel of [1] provides a practical implementation of the control strategy, thus it will be a useful asset in handling the actual execution of a passivity-based switching controller including model uncertainty compensation.…”