Risk-DTRRT-Based Optimal Motion Planning Algorithm for Mobile Robots

In this paper, an optimal motion planning algorithm and dynamic modeling of a planar kinematically redundant manipulator are considered. Kinematics of the manipulator is studied, Jacobian matrix is obtained and the dynamic equations are derived using D’Alembert’s principle. Also, a novel actuation method is introduced and applied to the 3-PRPR planar redundant manipulator. In this approach, the velocity of actuators is determined in such a way to minimize the 2-norm of the velocity vector, subjected to the derived kinematic relations as constraints. Having the optimal motion planning, the motion is controlled via a feedback linearization controller. The motion of the manipulator is simulated and the effectiveness of the proposed actuation strategy and the designed controller is investigated.

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EB-RRT: Optimal Motion Planning for Mobile Robots

IEEE Transactions on Automation Science and Engineering ◽

10.1109/tase.2020.2987397 ◽

2020 ◽

Vol 17 (4) ◽

pp. 2063-2073 ◽

Cited By ~ 2

Author(s):

Jiankun Wang ◽

Max Q.-H. Meng ◽

Oussama Khatib

Keyword(s):

Motion Planning ◽

Mobile Robots ◽

Optimal Motion ◽

Optimal Motion Planning

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Optimal Motion Planning Approach for Mobile Robot Navigation Problem

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.799-800.1078 ◽

2015 ◽

Vol 799-800 ◽

pp. 1078-1082

Author(s):

Bashra Kadhim Oleiwi ◽

Hubert Roth ◽

Bahaa I. Kazem

Keyword(s):

Motion Planning ◽

Mobile Robots ◽

Spline Interpolation ◽

Optimal Solution ◽

Mobile Robot Navigation ◽

Optimal Motion ◽

Navigation Problem ◽

Modified Genetic Algorithm ◽

Planning Approach ◽

Optimal Motion Planning

In this study, modified genetic algorithm (MGA) and A* search method (A*) is proposed for optimal motion planning of mobile robots. MGA utilizes the classical search and modified A* to establish a sub-optimal collision-free path as initial solution in simple and complex static environment. The enhancements for the proposed approach are presented in initialization stage and enhanced operators. Five objective functions are used to minimize traveling length, time, smoothness, security and trajectory and to reduce the energy consumption for mobile robots by using Cubic Spline interpolation curve fitting for optimal planned path. The purpose of this study is to evaluate the proposed approach performance by taking into consideration the effect of changing the number of iteration (it) and the size of population (pop) on its performance index. The simulation results show the effectiveness of proposed approach in governing the robot’s movements successfully from start to goal point after avoiding all obstacles its way in all tested environment. In addition, the results indicate that the proposed approach can find the optimal solution efficiently in a single run. This approach has been carried out by GUI using a popular engineering programming language, MATLAB.

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