Evolutionary multi-objective trajectory optimization for a redundant robot in Cartesian space considering obstacle avoidance

A method of end-effector trajectory planning in Cartesian space based on multi-objective optimization is proposed in this paper to solve the collision problem during the motion of the redundant manipulator. First, a cosine polynomial function is used to interpolate the trajectory of the end effector...

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Vydáno v:Mechanical Sciences Ročník 13; číslo 1; s. 41 - 53
Hlavní autoři: Liu, Yong, Li, Xiang, Jiang, Peiyang, Du, Zhe, Wu, Zhe, Sun, Boxi, Huang, Xinyan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Gottingen Copernicus GmbH 08.02.2022
Copernicus Publications
Témata:
Algorithms
Analysis
Cartesian coordinates
End effectors
Energy consumption
Genetic algorithms
Inverse kinematics
Kinematics
Manipulators
Materials of engineering and construction. Mechanics of materials
Mathematical optimization
Multiple objective analysis
Obstacle avoidance
Optimization algorithms
Particle swarm optimization
Polynomials
Researchers
Robotics
Robots
TA401-492
Trajectory optimization
Trajectory planning
Trigonometric functions
Velocity
ISSN:2191-916X, 2191-9151, 2191-916X
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Abstract A method of end-effector trajectory planning in Cartesian space based on multi-objective optimization is proposed in this paper to solve the collision problem during the motion of the redundant manipulator. First, a cosine polynomial function is used to interpolate the trajectory of the end effector, enabling it to reach the desired pose at a specific time. Then, the joint trajectory of the manipulator is solved by inverse kinematics, and the null space term is introduced as the joint limit constraint in the inverse kinematics equation. During the operation of the manipulator, the collision detection algorithm is employed to calculate the distance between the obstacle and each arm in real time. Finally, a multi-objective, multi-optimization model of trajectory that considers the obstacle avoidance, joint velocity, joint jerk and energy consumption is established and optimized with a multi-objective particle swarm optimization algorithm. The simulation results demonstrate that the proposed method can effectively accomplish the trajectory planning task and avoid obstacles; the joint trajectories obtained are smooth and meet the limit constraints; the joint jerk and energy consumption are well suppressed.
AbstractList A method of end-effector trajectory planning in Cartesian space based on multi-objective optimization is proposed in this paper to solve the collision problem during the motion of the redundant manipulator. First, a cosine polynomial function is used to interpolate the trajectory of the end effector, enabling it to reach the desired pose at a specific time. Then, the joint trajectory of the manipulator is solved by inverse kinematics, and the null space term is introduced as the joint limit constraint in the inverse kinematics equation. During the operation of the manipulator, the collision detection algorithm is employed to calculate the distance between the obstacle and each arm in real time. Finally, a multi-objective, multi-optimization model of trajectory that considers the obstacle avoidance, joint velocity, joint jerk and energy consumption is established and optimized with a multi-objective particle swarm optimization algorithm. The simulation results demonstrate that the proposed method can effectively accomplish the trajectory planning task and avoid obstacles; the joint trajectories obtained are smooth and meet the limit constraints; the joint jerk and energy consumption are well suppressed.
A method of end-effector trajectory planning in Cartesian space based on multi-objective optimization is proposed in this paper to solve the collision problem during the motion of the redundant manipulator. First, a cosine polynomial function is used to interpolate the trajectory of the end effector, enabling it to reach the desired pose at a specific time. Then, the joint trajectory of the manipulator is solved by inverse kinematics, and the null space term is introduced as the joint limit constraint in the inverse kinematics equation. During the operation of the manipulator, the collision detection algorithm is employed to calculate the distance between the obstacle and each arm in real time. Finally, a multi-objective, multi-optimization model of trajectory that considers the obstacle avoidance, joint velocity, joint jerk and energy consumption is established and optimized with a multi-objective particle swarm optimization algorithm. The simulation results demonstrate that the proposed method can effectively accomplish the trajectory planning task and avoid obstacles; the joint trajectories obtained are smooth and meet the limit constraints; the joint jerk and energy consumption are well suppressed.
Audience Academic
Author Boxi Sun
Zhe Du
Yong Liu
Zhe Wu
Xinyan Huang
Peiyang Jiang
Xiang Li
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CitedBy_id crossref_primary_10_1007_s11431_024_2841_y
crossref_primary_10_1007_s40435_022_01033_0
crossref_primary_10_3390_aerospace10010013
crossref_primary_10_1177_09544062241266149
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Snippet A method of end-effector trajectory planning in Cartesian space based on multi-objective optimization is proposed in this paper to solve the collision problem...
A method of end-effector trajectory planning in Cartesian space based on multi-objective optimization is proposed in this paper to solve the collision problem...
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StartPage 41
SubjectTerms Algorithms
Analysis
Cartesian coordinates
End effectors
Energy consumption
Genetic algorithms
Inverse kinematics
Kinematics
Manipulators
Materials of engineering and construction. Mechanics of materials
Mathematical optimization
Multiple objective analysis
Obstacle avoidance
Optimization algorithms
Particle swarm optimization
Polynomials
Researchers
Robotics
Robots
TA401-492
Trajectory optimization
Trajectory planning
Trigonometric functions
Velocity
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Title Evolutionary multi-objective trajectory optimization for a redundant robot in Cartesian space considering obstacle avoidance
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