A robust synergetic controller for Quadrotor obstacle avoidance using Bézier curve versus B-spline trajectory generation

2022 ◽  
Author(s):  
Chara kheireddine ◽  
Abdessemed Yassine ◽  
Srairi Fawzi ◽  
Mokhtari Khalil
Keyword(s):  
Obstacle Avoidance ◽  
Trajectory Generation ◽  
Bézier Curve ◽  
Bezier Curve ◽  
B Spline ◽  
Curve Versus

scholarly journals Obstacle Avoidance Techniques for Robot Path Planning

2019 ◽  
Vol 12 (1) ◽  
pp. 56-65
Author(s):  
Ali N. Abdulnabi
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Robot Manipulator ◽  
Optimal Path ◽  
Initial Point ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Robot Arm ◽  
Starting Position ◽  
Elapsed Time

This paper presents a collision-free path planning approaches based on Bézier curve and A-star algorithm for robot manipulator system. The main problem of this work is to finding a feasible collision path planning from initial point to final point to transport the robot arm from the preliminary to the very last within the presence of obstacles, a sequence of joint angles alongside the path have to be determined. To solve this problem several algorithms have been presented among which it can be mention such as Bug algorithms, A-Star algorithms, potential field algorithms, Bézier curve algorithm and intelligent algorithms. In this paper obstacle avoidance algorithms were proposed Bézier and A-Star algorithms, through theoretical studies and simulations with several different cases, it's found verify the effectiveness of the methods suggested. It's founded the Bézier algorithm is smoothing accurate, and effective as compare with the A-star algorithm, but A-star is near to shortest and optimal path to free collision avoidance. The time taken and the elapsed time to traverse from its starting position and to reach the goal are recorded the tabulated results show that the elapsed time with different cases to traverse from the start location to destination using A-star Algorithm is much less as compared to the time taken by the robot using Bézier Algorithm to trace the same path. The robot used was the Lab-Volt of 5DOF Servo Robot System Model 5250 (RoboCIM5250)

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.

scholarly journals Approximating curve by a single segment of B-Spline or Bézier curve directly in CAD environment

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mariusz Sobolak ◽  
Piotr Połowniak ◽  
Adam Marciniec ◽  
Patrycja Ewa Jagiełowicz
Keyword(s):  
Simulated Annealing ◽  
Optimization Methods ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Control Points ◽  
Curve Segment ◽  
B Spline ◽  
Single Segment ◽  
Original Procedure ◽  
The Given

AbstractThe paper presents the method of approximating curves with a single segment of the B-Spline and Bézier curves. The method for determining a single curve segment using the optimization methods in the CATIA environment is shown. The algorithms of simulated annealing and design of experiment are used for optimization. For the same purpose, a new original procedure for determining the distance between the given curves using explicit parameters in the CATIA environment was also used. This approximation of the cyclic curves results in the curve oscillation as shown in the examples. The results show that the approximation method with Bézier curve using control points as “free” points can be applied to obtain the best results of approximation.

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 ◽  
Integrated Optimization

Abstract A super redundant serpentine manipulator has slender structure and multiple degrees of freedom. It can travel through narrow spaces and move in complex spaces. 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 an integrated optimization method to solve the path planning for obstacle avoidance and discrete trajectory tracking of a super redundant manipulator. In this integrated optimization, path planning is established on a Bezier curve, and particle swarm optimization is adopted to adjust the control points of the Bezier curve with the kinematic constraints of manipulator. A feasible obstacle avoidance path is obtained along with a discrete trajectory tracking by 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 integrated 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.

Sign in / Sign up

Export Citation Format

Share Document