Control Strategy For Mobile Robot Research Articles

Multi-Agent Reinforcement Learning Tracking Control of a Bionic Wheel-Legged Quadruped

This paper presents a novel approach to developing control strategies for mobile robots, specifically the Pegasus, a bionic wheel-legged quadruped robot with unique chassis mechanics that enable four-wheel independent steering and diverse gaits. A multi-agent (MA) reinforcement learning (RL) controller is proposed, treating each leg as an independent agent with the goal of autonomous learning. The framework involves a multi-agent setup to model torso and leg dynamics, incorporating motion guidance optimization signal in the policy training and reward function. By doing so, we address leg schedule patterns for the complex configuration of the Pegasus, the requirement for various gaits, and the design of reward functions for MA-RL agents. Agents were trained using two variations of policy networks based on the framework, and real-world tests show promising results with easy policy transfer from simulation to the actual hardware. The proposed framework models acquired higher rewards and converged faster in training than other variants. Various experiments on the robot deployed framework showed fast response (0.8 s) under disturbance and low linear, angular velocity, and heading error, which was 2.5 cm/s, 0.06 rad/s, and 4°, respectively. Overall, the study demonstrates the feasibility of the proposed MA-RL control framework.

Path Planning Method and Control of Mobile Robot with Uncertain Dynamics Based on Improved Artificial Potential Field and Its Application in Health Monitoring

To enhance the navigation and control efficiency of mobile robots in the field of health monitoring, a novel path planning and control strategy for mobile robots with uncertain dynamics based on improved artificial potential fields is proposed in this paper. Specifically, we propose an attractive potential field rotation method to overcome the limitation that traditional artificial potential fields tend to fall into local minima. Then, we define a new class of attractive potential fields to address the goals non-reachable with obstacles nearby (GNRON) and collisions caused by excessive attractive force at long distances from the target point. Furthermore, a control law is proposed for the mobile robot with uncertain dynamics, and the stability of the closed-loop system is rigorously proven using the Lyapunov method. Finally, the feasibility and effectiveness of the proposed method are verified by simulations and experiments.

A sEMG-Based Shared Control System With No-Target Obstacle Avoidance for Omnidirectional Mobile Robots

We propose a novel shared control strategy for mobile robots in a human-robot interaction manner based on surface eletromyography (sEMG) signals. For security reasons, an obstacle avoidance scheme is introduced to the shared control system as collision avoidance guidance. The motion of the mobile robot is a resultant of compliant motion control and obstacle avoidance. In the mode of compliant motion, the sEMG signals obtained from the operator's forearms are transformed into human commands to control the moving direction and linear velocity of the mobile robot, respectively. When the mobile robot is blocked by obstacles, the motion mode is converted into obstacle avoidance. Aimed at the obstacle avoidance problem without a specific target, we develop a no-target Bug (NT-Bug) algorithm to guide the mobile robot to avoid obstacles and return to the command line. Besides, the command moving direction given by the operator is taken into consideration in the obstacle avoidance process to plan a smoother and safer path for the mobile robot. A model predictive controller is exploited to minimize the tracking errors. Experiments have been implemented to demonstrate the effectiveness of the proposed shared control strategy and the NT-Bug algorithm.

Optimal Threshold Setting for Event-Based Control Strategies

In this paper, an event-based control strategy for mobile robots is proposed. The solution includes new features that minimize the effects of the noise on the system. Two methodologies have been developed to compensate the perturbations. To avoid the effects of such perturbations, a threshold calculator and a perturbation estimator are included in the system. The proposed system is compared with classical control systems based on discrete time. Different scenarios are analyzed in the experiments to check its performance. The stability and the improvements of the proposed control strategy are also analyzed in the experimental results.

Wheeled Mobile Robot Trajectory Tracking using Sliding Mode Control

This paper introduces and discusses a control strategy for nonholonomic wheeled mobile robots. The models of the robots include the kinematic and dynamic equations of motion. Trajectory tracking control problem of parallel wheeled differential drive mobile robot is considered, where the robot should reach the final position by following a referenced trajectory for different initial conditions. A motion control strategy for a mobile robot by only assuming the kinematic model was developed by many researchers. In the case of high-speed robot motion, the dynamical model is important. In this study, two stages of the proposed control strategy are presented. The first one is dealing with the kinematics of the system and denoted as ‘steering’ controller. The second one, a velocity controller is developed based on the robust sliding mode control technique. A new design of the sliding surface is proposed. The switching feedback gain is determined based on a novel mathematical simple rule, considering the initial state of the system. Robustness to parameters uncertainties and stability of the controlled system are achieved. A simulation model of the controlled system is developed in MATLAB-SIMULINK software. Simulation results show the performances of the developed controller. In the case of presence of uncertainties, the results show the superiority of the proposed controller compared with the computed torque method.

Event-Based Control Strategy for Mobile Robots in Wireless Environments.

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy.

Mobile robot path planning based on adaptive bacterial foraging algorithm

The utilization of biomimicry of bacterial foraging strategy was considered to develop an adaptive control strategy for mobile robot, and a bacterial foraging approach was proposed for robot path planning. In the proposed model, robot that mimics the behavior of bacteria is able to determine an optimal collision-free path between a start and a target point in the environment surrounded by obstacles. In the simulation, two test scenarios of static environment with different number obstacles were adopted to evaluate the performance of the proposed method. Simulation results show that the robot which reflects the bacterial foraging behavior can adapt to complex environments in the planned trajectories with both satisfactory accuracy and stability.

Neural Network-Based Optimal Control of Mobile Robot Formations With Reduced Information Exchange

A novel formation control scheme for mobile robots is introduced in the context of leader-follower framework with reduced communication exchange. The dynamical controller inputs for the robots are approximated from nonlinear optimal control techniques in order to track the designed control velocities generated by the kinematic controller. The proposed nonlinear optimal control technique, referred to as adaptive dynamic programming, uses neural networks (NNs) to solve the optimal formation control problem in discrete time in the presence of unknown internal dynamics and a known control coefficient matrix. A modification to the follower's kinematic controller is used to allow the desired formation to change in order to navigate around obstacles. The proposed obstacle avoidance technique modifies the desired separation and bearing of the follower to guide the follower around obstacles. Minimal wireless communication is utilized between the leader and the follower to allow the follower to approximate and compensate for the formation dynamics. All NNs are tuned online, and the stability of the entire formation is demonstrated using Lyapunov methods. Hardware results demonstrate the effectiveness of our approach.

Homography-Based Control Scheme for Mobile Robots With Nonholonomic and Field-of-View Constraints

In this paper, we present a visual servo controller that effects optimal paths for a nonholonomic differential drive robot with field-of-view constraints imposed by the vision system. The control scheme relies on the computation of homographies between current and goal images, but unlike previous homography-based methods, it does not use the homography to compute estimates of pose parameters. Instead, the control laws are directly expressed in terms of individual entries in the homography matrix. In particular, we develop individual control laws for the three path classes that define the language of optimal paths: rotations, straight-line segments, and logarithmic spirals. These control laws, as well as the switching conditions that define how to sequence path segments, are defined in terms of the entries of homography matrices. The selection of the corresponding control law requires the homography decomposition before starting the navigation. We provide a controllability and stability analysis for our system and give experimental results.

Remote secure decentralized control strategy for mobile robots

The main goal of this paper is to define, study and analyze a remote control architecture for a set of non-holonomic robotic vehicles. This project gathers three laboratories and the French Army Research Office. Each of these laboratories deals with a part of this multidisciplinary project which includes coordinated control, control architecture, control with time delay and monitoring of the wireless network. In this paper, we present the whole goal of this project including the basic experimental setup developed to validate our control algorithm. We also focus on a new decentralized control strategy that uses the Leader–Follower principle. The originality of this paper stems from the use of the signal level of wireless connection as a control vector. Indeed, each vehicle is fitted with two wireless devices. One of them is equipped with a sector antenna fitted on a DC motor to track the direction of best reception. Thus, it allows us to find the relative angular position of the Follower pointing out the Leader. Using wireless technology as a sensor, instead of vision for instance, allows a longer distance of the coordinated control loop between each vehicle (approximately 100 m) even if GPS information is not available.

Dynamic Modelling and Adaptive Traction Control for Mobile Robots

Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

An Adaptive PI Control System for an Omnidirectional Mobile Robot

Resolved acceleration and PID control provide high-performance control in an omnidirectional mobile robot, but most research does not consider plant parameter perturbations requiring that control gains be readjusted. We present an adaptive PI control strategy for mobile robots that automatically adjusts PI controller parameters based on error signals. Experiments verify the effectiveness of our method.