Obstacle Avoidance and Trajectory Tracking Using Fluid-Based Approach in 2D Space

2012 ◽  
pp. 293-304 ◽  
Author(s):  
Paweł Szulczyński ◽  
Dariusz Pazderski ◽  
Krzysztof R. Kozłowski
Keyword(s):  
Obstacle Avoidance ◽  
Trajectory Tracking ◽  
2D Space

Quadrotor trajectory tracking and obstacle avoidance by chaotic grey wolf optimization- based backstepping control with sliding mode extended state observer

2020 ◽  
Vol 42 (9) ◽  
pp. 1675-1689 ◽  
Author(s):  
Yingxun Wang ◽  
Yan Ma ◽  
Zhihao Cai ◽  
Jiang Zhao
Keyword(s):  
Obstacle Avoidance ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Backstepping Control ◽  
Extended State Observer ◽  
Grey Wolf ◽  
Extended State ◽  
Grey Wolf Optimization ◽  
Control Scheme ◽  
Virtual Target

In this paper, a new swarm intelligent-based backstepping control scheme is proposed for quadrotor trajectory tracking and obstacle avoidance. First, the sliding mode extended state observer (SMESO) is used to estimate different disturbances, and the tracking differentiator (TD) is integrated to enhance the performance of backstepping control scheme. Then, the chaotic grey wolf optimization (CGWO) is developed with chaotic initialization and chaotic search to optimize the parameters of attitude and position controllers. Further, the virtual target guidance approach is proposed for quadrotor trajectory tracking and obstacle avoidance. Comparative simulations and Monte Carlo tests are carried out to demonstrate the effectiveness and robustness of the CGWO-based backstepping control scheme and virtual target guidance approach.

scholarly journals Obstacle avoidance and multitarget tracking of a super redundant modular manipulator based on Bezier curve and particle swarm optimization

2020 ◽  
Author(s):  
Chen Li ◽  
Ying Ma ◽  
Yu Zhang ◽  
Jinguo Liu
Keyword(s):  
Particle Swarm Optimization ◽  
Obstacle Avoidance ◽  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Optimization Method ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Redundant Manipulator ◽  
Swarm Optimization ◽  
Composite Optimization

Abstract A super redundant serpentine manipulator has slender structure and multiple degrees of freedom and can travel through narrow space and move in complex space. This manipulator is composed of many modules that can form different lengths of robot arms for different application sites. The increase in degrees of freedom causes the inverse kinematics of redundant manipulator to be typical and immensely increases the calculation load in the joint space. This paper presents a composite optimization method of path planning for obstacle avoidance and discrete trajectory tracking of a super redundant manipulator. In this composite optimization, path planning is established on a Bezier curve, particle swarm optimization is adopted to adjust the control points of the Bezier curve with the kinematic constraints of manipulator, and a feasible obstacle avoidance path is obtained along with a discrete trajectory tracking using a follow-the-leader strategy. The relative distance between each two discrete path points is limited to reduce the fitting error of the connecting rigid links to the smooth curve. Simulation results show that this composite optimization method can rapidly search for the appropriate trajectory to guide the manipulator in obtaining the target while achieving obstacle avoidance and meeting joint constraints. The proposed algorithm is suitable for 3D space obstacle avoidance and multitarget path tracking.

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