Robust Intelligent Active Force Control Of Nonholonomic Wheeled Mobile Robot

Tang, Huiqiang; Mailah, Musa; Jalil, M. Kasim A.

doi:10.11113/jt.v44.375

Cited by 4 publications

(8 citation statements)

References 12 publications

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“…The purpose of Motion Planning is to enable the robot user to specify the desired high level activity with the system itself that fills in the missing low level details [4]. This motion planning consists of the following two parts:…”

Section: Motion Planningmentioning

confidence: 99%

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An Integrated Technique for Trajectory Planning of Non-Holonomic Mobile Robot in Unstructured Environment

Arshad

Choudhry

2006

2006 IEEE International Multitopic Conference

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Path planning is an important issue in mobile robots. When the environment consists of obstacles, Path planning is to find a collision free path for mobile robot to move from starting position to the target location. This Path planning should be optimal or must be near-optimal with respect to time, distance or energy. But distance is the most commonly adopted criterion. In this paper a new approach for the representation of dynamic environment has been presented. The integration of stationary and moving obstacles is the new work presented in this paper. Uncertainty in environment estimation has been taken into account by the probabilistic reasoning technique. Occupancy or risk of the probabilistic grid representation has been estimated for each cell using sensor data.

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Section: Motion Planningmentioning

confidence: 99%

“…Motion planning breaks down high-level control tasks into low level motion execution commands [4]. At higher-level the motion planning is responsible for the generation of a collision-free non-holonomic trajectory with respect to the time optimality and the workspace layout.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Technique for Trajectory Planning of Non-Holonomic Mobile Robot in Unstructured Environment

Arshad

Choudhry

2006

2006 IEEE International Multitopic Conference

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“…[16][17][18][19] The method depends on the measurements of the applied torque and acceleration plus a good approximation of the estimated inertia matrix to estimate the force feedback of the control system. [20][21][22] Luy has proposed an optimal algorithm to solve the problem of unknown or uncalibrated disturbances for nonholonomic mobile multirobot (NMMR) using an omnidirectional vision sensor. 23 The optimal tracking using both the system kinematics and dynamics has been initially transformed into equivalent optimal control for disturbance rejection.…”

Section: Introductionmentioning

confidence: 99%

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

Ali

Mailah

2019

International Journal of Advanced Robotic Systems

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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.

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“…Different control schemes have been proposed for tracking control of the mobile robots such as intelligent methods. 2,3 In recent years, fuzzy logic has been applied in the controller designs to cope with different uncertainty problems in the system. In ref.…”

Section: Introductionmentioning

confidence: 99%

Teaching–learning-based optimal interval type-2 fuzzy PID controller design: a nonholonomic wheeled mobile robots

2013

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SUMMARYThis paper introduces an optimal interval type-2 fuzzy proportional–integral–derivative (PID) controller to achieve the best trajectory tracking for nonholonomic wheeled mobile robots (WMRs). In the core of the proposed method, a novel population-based optimization algorithm, called teaching–learning-based optimization (TLBO), is employed for evolving the parameters of the controller as well as the parameters of the input and output membership functions. Two PID controllers are designed for each of two wheels separately whereas each controller has two inputs and one output that are logically connected by nine rules. The controller can handle the problem of integrated kinematic and dynamic tracking in the presence of uncertainties. Simulation results demonstrate the superiority of the proposed control scheme.

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Robust Intelligent Active Force Control Of Nonholonomic Wheeled Mobile Robot

Cited by 4 publications

References 12 publications

An Integrated Technique for Trajectory Planning of Non-Holonomic Mobile Robot in Unstructured Environment

An Integrated Technique for Trajectory Planning of Non-Holonomic Mobile Robot in Unstructured Environment

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

Teaching–learning-based optimal interval type-2 fuzzy PID controller design: a nonholonomic wheeled mobile robots

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