Motion Control Of Mobile Robot Research Articles

Bio-inspired Approach for Smooth Motion Control of Wheeled Mobile Robots

Wheeled mobile robot (WMR) has gained wide application in civilian and military fields. Smooth and stable motion of WMR is crucial not only for enhancing control accuracy and facilitating mission completion, but also for reducing mechanical tearing and wearing. In this paper, we present a novel bio-inspired approach aiming at significantly reducing motion chattering phenomena inherent with traditional methods. The main idea of the proposed smooth motion controller is motivated by two famous Chinese sayings “haste does not bring success” and “ride softly then you may get home sooner”, which inspires the utilization of pre-processing the speed commands with the help of fuzzy rules to generate more favorable movement for the actuation device, so as to effectively avoid the jitter problem that has not yet been adequately solved by traditional methods. Detail formulas and algorithms are derived with consideration of the kinematics and dynamics of WMR. Smooth and asymptotically stable tracking of the WMR along the desired position and orientation is ensured and real-time experiment demonstrates the effectiveness and simplicity of the proposed method.

Policy Feedback for the Refinement of Learned Motion Control on a Mobile Robot

Motion control is fundamental to mobile robots, and the associated challenge in development can be assisted by the incorporation of execution experience to increase policy robustness. In this work, we present an approach that updates a policy learned from demonstration with human teacher feedback. We contribute advice-operators as a feedback form that provides corrections on state-action pairs produced during a learner execution, and Focused Feedback for Mobile Robot Policies (F3MRP) as a framework for providing feedback to rapidly-sampled policies. Both are appropriate for mobile robot motion control domains. We present a general feedback algorithm in which multiple types of feedback, including advice-operators, are provided through the F3MRP framework, and shown to improve policies initially derived from a set of behavior examples. A comparison to providing more behavior examples instead of more feedback finds data to be generated in different areas of the state and action spaces, and feedback to be more effective at improving policy performance while producing smaller datasets.

Motion Control of Caster-Type Passive Mobile Robot with Servo Brakes

In this paper, we introduce a passive mobile robot called prototype Caster-Type Passive Robot Porter (C-PRP), which is developed on the basis of a concept of passive robotics. This mobile robot consists of two casters with servo brakes and one passive rigid wheel. Prototype C-PRP has passive dynamics with respect to the force applied by a human and controls its appropriate motion with the servo brakes. We derive the feasible braking force/moment applied to the robot on the basis of the characteristics of the servo brakes. This paper especially focuses on a fundamental motion control algorithm based on the feasible braking force/moment. We realize the path tracking function and the collision avoidance function as examples by applying the proposed algorithm to prototype C-PRP. These functions are implemented to prototype C-PRP actually, and experimental results confirm its validity.

Dynamic consensus of high-order multi-agent systems and its application in the motion control of multiple mobile robots

In this paper, the leader-following consensus problem for multi-agent linear dynamic systems is considered. All agents and leader have identical multi-input multi-output (MIMO) linear dynamics that can be of any order, and only the output information of each agent is delivered throughout the communication network. When the interaction topology is fixed, the leader-following consensus is attained by H ? dynamic output feedback control, and the sufficient condition of robust controllers is equal to the solvability of linear matrix inequality (LMI). The whole analysis is based on spectral decomposition and an equivalent decoupled structure achieved, and the stability of the system is proved. Finally, we extended the theoretical results to the case that the interaction topology is switching. The simulation results for multiple mobile robots show the effectiveness of the devised methods.

Coordination of Multiple Control Schemes for Mobile Robot Navigation on the Basis of the Generalized Stochastic Petri-Nets

There have been two major streams of research for the motion control of mobile robots: model-based deliberate control and sensor-based reactive control. Since the two schemes have complementary advantages and disadvantages, each cannot completely replace the other. There are a variety of environmental conditions that affect the performance of navigation. The motivation of this study is that multiple motion control schemes are required to survive in dynamic real environments. In this paper, we exploit two discrete motion controllers for mobile robots. One is the deliberate trajectory tracking controller and the other is the reactive dynamic window approach. We propose the selective coordination of two controllers on the basis of the generalized stochastic Petri net (GSPN) framework. The major scope of this paper is to clarify the advantage of the proposed controller based on the coordination of multiple controllers from the results of quantitative performance comparison among motion controllers. For quantitative comparison, both simulations and experiments in dynamic environments were carried out. In addition, it is shown that navigation experiences are accumulated in the GSPN formalism. The performance of navigation service can be significantly improved owing to the automatically stored experiences.

A new procedure for multi-mode sequential flocking with application to multiple non-holonomic mobile robot motion control: implementation and analysis

This is the second of a two-part paper that investigates the multi-mode sequential flocking with application to multiple non-holonomic mobile robot motion control. In this part, a multiple mobile robotsimulation system based on MuRoS is used to simulate the real multiple mobile robots running environment. Furthermore, an analysis method of the flocking system based on ‘minimum stable time’ is proposed, which can be employed to analyse the performance of multi-mode sequential flocking of mobile robots team. At last, bench tests have been comprehensively conducted to demonstrate the efficacy of the proposed procedures on efficient collision and obstacle avoidance in flocking motion, which were described in the first part.

A new procedure for multi-mode sequential flocking with application to multiple non-holonomic mobile robot motion control: mode description and integration principle

This is the first of two-part paper that investigates the multi-mode sequential flocking with application to multiple non-holonomic mobile robot motion control. To provide a new procedure to avoid collisions and obstacles in the process of multi-robot’s sequential flocking, this paper presents the design of a multi-model flocking control for multiple mobile robots in terms of behaviour-based robotics. Some nature-imitating behaviour modes are integrated into the new sequential flocking strategy, including single-robot potential-based behaviour, single-robot wall-following behaviour, multi-robot rigid-body bouncing behaviour, multi-robot path-tracking behaviour and their fusion state. In this way, the efficient collision and obstacle avoidance in flocking motion can be achieved.

Motion Control of Mobile Robot Based on Immune Clonal Algorithm Evolved by Virus

To solve the motion control of mobile robot, a PID control optimized by improved immune clonal algorithm is presented. On the basis of immune clonal algorithm, a new virus evolutionary clonal algorithm (VECA) is provided firstly. The VECA focuses on the virus infection of population after immune mutation, which improves the population diversity and strengths the local search ability of immune clonal algorithm. Then the proposed VECA is used to optimize the algorithm parameters of PID control strategy for the robot motion. The simulation results show that VECA can realize the optimization of PID parameters and improve the control precision of path track.

Model-based PI–fuzzy control of four-wheeled omni-directional mobile robots

The purpose of this study is to suggest and examine a PI–fuzzy path planner and associated low-level control system for a linear discrete dynamic model of omni-directional mobile robots to obtain optimal inputs for drivers. Velocity and acceleration filtering is also implemented in the path planner to satisfy planning prerequisites and prevent slippage. Regulated drivers’ rotational velocities and torques greatly affect the ability of these robots to perform trajectory planner tasks. These regulated values are examined in this research by setting up an optimal controller. Introducing optimal controllers such as linear quadratic tracking for multi-input–multi-output control systems in acceleration and deceleration is one of the essential subjects for motion control of omni-directional mobile robots. The main topics presented and discussed in this article are improvements in the presented discrete-time linear quadratic tracking approach such as the low-level controller and combined PI–fuzzy path planner with appropriate speed monitoring algorithm such as the high-level one in conditions both with and without external disturbance. The low-level tracking controller presented in this article provides an optimal solution to minimize the differences between the reference trajectory and the system output. The efficiency of this approach is also compared with that of previous PID controllers which employ kinematic modeling. Utilizing the new approach in trajectory-planning controller design results in more precise and appropriate outputs for the motion of four-wheeled omni-directional mobile robots, and the modeling and experimental results confirm this issue.

Motion planning algorithms of an omni-directional mobile robot with active caster wheels

This work deals with motion planning algorithms of an omni-directional mobile robot with active caster wheels. A typical problem occurred in the motion control of such omni-directional mobile robot, which has been identified through experimental experiences, is skidding of the mobile wheel. It sometimes results in uncertain rotation of the steering wheel. To cope with this problem, a motion planning algorithm which resolves the skidding problem and uncertain motions of the steering wheel is mainly investigated. For navigation of the mobile robot, the posture of the omni-directional mobile robot is initially calculated using the odometry information. Then, the accuracy of the mobile robot's odometry is measured through comparison of the odometry information and the external sensor measurement. Finally, for successful navigation of the mobile robot, a motion planning algorithm that employs kinematic redundancy resolution method is proposed. Through simulations and experimentation, the feasibility of proposed algorithms was verified.

Adaptive Trajectory Tracking Control for a Nonholonomic Mobile Robot

As one of the core issues of the mobile robot motion control, trajectory tracking has received extensive attention. At present, the solution of the problem only takes kinematic or dynamic model into account separately, so that the presented strategy is difficult to realize satisfactory tracking quality in practical application. Considering the unknown parameters of two models, this paper presents an adaptive controller for solving the trajectory tracking problem of a mobile robot. Firstly, an adaptive kinematic controller utilized to generate the command of velocity is designed based on Backstepping method. Then, in order to make the real velocity of mobile robot reach the desired velocity asymptotically, a dynamic adaptive controller is proposed adopting reference model and Lyapunov stability theory. Finally, through simulating typical trajectories including circular trajectory, fold line and parabola trajectory in normal and perturbed cases, the results illustrate that the control scheme can solve the tracking problem effectively. The proposed control law, which can tune the kinematic and dynamic model parameters online and overcome external disturbances, provides a novel method for improving trajectory tracking performance of the mobile robot.

Extended Kalman and Particle Filtering for sensor fusion in motion control of mobile robots

Motion control of mobile robots and efficient trajectory tracking is usually based on prior estimation of the robots’ state vector. To this end Gaussian and nonparametric filters (state estimators from position measurements) have been developed. In this paper the Extended Kalman Filter which assumes Gaussian measurement noise is compared to the Particle Filter which does not make any assumption on the measurement noise distribution. As a case study the estimation of the state vector of a mobile robot is used, when measurements are available from both odometric and sonar sensors. It is shown that in this kind of sensor fusion problem the Particle Filter has better performance than the Extended Kalman Filter, at the cost of more demanding computations.

The Null-Space-based Behavioral Control for Mobile Robots with Velocity Actuator Saturations

In this paper we present the application of the Null-Space-based Behavioral (NSB) approach to the motion control of mobile robots with velocity saturated actuators. The NSB is a behavior-based robot control approach that uses a hierarchical organization of the tasks to guarantee that they are executed according to a desired priority: it uses a projection technique to avoid that, in the absence of actuator saturations, low-priority tasks could influence higher-priority tasks. The main contribution of this paper is the extension of the NSB approach to the case where actuator velocity saturation bounds are explicitly taken into account. The proposed solution dynamically scales task velocity commands so that the hierarchy of task priorities is preserved in spite of actuator velocity saturations. The approach has been validated on two specific case studies. In the first case, the NSB elaborates the motion directives for a single mobile robot that has to reach a target while avoiding a point obstacle1 in this case, the mission is composed of two tasks. In the second case, the NSB elaborates the motion directives for a team of six mobile robots that has orates the motion directives for a team of six mobile robots that has to entrap and escort a target1 in this case the mission is composed of four tasks. The approach is validated by numerical simulations and by experiments with real mobile robots.

Two-wheeled mobile robot motion control in dynamic environments

In this paper, a feedback control scheme of a two-wheeled mobile robot is explored in dynamic environments. In the existence of local minima, the design of controller is based on Lyapunov function candidate and considers virtual forces information including detouring force. Simulation results are presented to show the effectiveness of the proposed control scheme.

Motion and Internal Force Control for Omnidirectional Wheeled Mobile Robots

This paper presents an integrated scheme for motion control and internal force control for a redundantly actuated omnidirectional wheeled mobile robot. The interactive forces between a robot body and its wheels can be reduced into two orthogonal parts: motion-induced forces and internal forces. First, it is shown that the internal forces reside in the null space of the coefficient matrix of the interactive forces and do not affect robotic motion. However, these forces caused by motor torques should be minimized as much as possible to increase the energy efficiency and life span of joint components. With different goals, the control for motion and the control for internal forces can be designed separately. Here, both kinematic and dynamic models of the forces are proposed. A proportional differential plus controller regulates the motion and an inverse dynamic controller tracks it. Then, to minimize the internal forces, an integral feedback internal force controller is used. The motion controller guarantees the robotic motion while the internal force controller minimizes the internal force occurring during robot motion. Simulation results verify the effectiveness of the proposed schemes.

Control Algorithm for Four-Wheeled Robot Motionfor Monit oring Problems

Monitoring and surveillance by means of mobile robots are of great importance in a number of various applications. The level of technology and science development is high enough to use robotic vehicle for monitoring in dangerous or hard-to-reach areas, for continuous surveillance of large industrial objects, in military purposes. The main problems in this area are navigation and control of vehicle. The majority of articles are dedicated to problems of motion control of wheeled mobile robots with two or three wheels [1-2]. As to four-wheeled mobile robots its kinematics and dynamics are considered in [3].

Motion control and navigation of multiple mobile robots for obstacle avoidance and target seeking: A rule-based neuro-fuzzy technique

This paper describes a rule-based neuro-fuzzy technique for the navigation of 1000 robots in a cluttered environment. The planning and coordination between the mobile robots is extremely difficult. In the present analysis rule-based and rule-based neuro-fuzzy techniques are used to navigate multiple mobile robots in unknown and partially known environments. The aim of the robots is to reach a predefined goal. Based upon a reference motion, direction, distances between the robots and obstacles, and distances between the robots and targets, different types of rules are defined heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and an attracting influence between the robots and targets. Then a hybrid rule-based neuro-fuzzy technique is analysed to find the steering angle of the robots. Simulation and experimental results show that the proposed rule-based neuro-fuzzy technique shows a better navigation performance in complex and unknown environments than the simple rule-based technique.

Support vector machine-based two-wheeled mobile robot motion control in a noisy environment

In this paper, a support vector machine (SVM)-based control scheme of a two-wheeled mobile robot is proposed in a noisy environment. The noisy environment is defined as the measured data with uncertainty. The proposed control scheme can control the robot by consideration of local minima, where the controller is based on the Lyapunov function candidate and considers virtual force information. The SVM method is used for estimating the control parameters from the noisy environment. Four simulation results are presented to show the effectiveness of the proposed control scheme in the noisy environment, while the performance of a former method degrades significantly.

The stable and precise motion control for multiple mobile robots

Intelligent path planning of multiple mobile robots has been addressed in this paper. Cooperative behaviour can be achieved using several mobile robots, which require online inter-communication among themselves. In the present investigation rule-based and rule-based-neuro-fuzzy techniques are analyzed for multiple mobile robots navigation in an unknown or partially known environment. The final aims of the robots are to reach some pre-defined goals. Based upon a reference motion, direction; distances between the robots and obstacles; distances between the robots and targets; different types of rules are taken heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and with an attracting influence between the robots and targets. Then a hybrid rule-based-neuro-fuzzy technique is analyzed to find the steering angle of the robots. Results show that the proposed rule-based-neuro-fuzzy technique can improve navigation performance in complex and unknown environments compared to this simple rule-based technique.

Motion control of mobile wheeled robots

A vector-matrix formalism of nonholonomic mechanics is set up, which is used to construct mathematical models of mobile wheeled robots. The properties of free (ballistic) motions of mobile robots, which can be the basis of natural motion control modes, are studied. The analysis of uncontrollable motions is carried out, taking transients in circuits of the electric drive into consideration. The problem of determining voltages supplied to drives of the robot that ensure implementation of program motions is discussed. One candidate solution of a problem of planning a pathway of the robot in an ordered medium is presented. A mobile single-wheeled robot with a gyroscopic stabilization system is described—the “Gyrowheel” robot, capable of moving autonomously along a straight-line (rectilinear motion), as well as along a curvilinear pathway.