Mechanical arm path planning method based on simulated annealing genetic algorithm

A genetic algorithm and simulated annealing technology, applied in the field of robotic arm path planning based on simulated annealing genetic algorithm, can solve the problems of low search efficiency, premature convergence, large dimension, etc., and achieve the effect of improving solution accuracy and convergence speed

Inactive Publication Date: 2018-11-23
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

Due to the large dimension, it is difficult to adopt the trajectory optimization algorithm, and it o

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  • Mechanical arm path planning method based on simulated annealing genetic algorithm
  • Mechanical arm path planning method based on simulated annealing genetic algorithm
  • Mechanical arm path planning method based on simulated annealing genetic algorithm

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Embodiment Construction

[0049] The present invention is further described below in conjunction with accompanying drawing:

[0050] see figure 1 , a method for path planning of a manipulator based on a simulated annealing genetic algorithm, including the following steps:

[0051] Step 1: Use the Lagrangian method to model the position-level and velocity-level kinematics and dynamics of the space six-degree-of-freedom manipulator;

[0052] Step 2: According to the extremely short-time collision model at the end of the manipulator, the disturbance of the base caused by the instantaneous collision and the constraints of the joint angles of the manipulator, establish the optimal fitness function of the manipulator trajectory;

[0053] Step 3: Use the fifth-order polynomial to fit the path of the manipulator, and use the simulated annealing genetic algorithm to solve the optimal trajectory to meet a better fitness function.

[0054] In step 1, the Lagrangian method is used to establish a six-degree-of-fr...

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Abstract

The invention discloses a mechanical arm path planning method based on a simulated annealing genetic algorithm. The method comprises the following steps that step 1: a Lagrange method is adopted to conduct position level, velocity level kinetics and kinetics modeling on a space six-degree-of-degree mechanical arm; step 2: regarding the disturbance generated on a base and the constraint of all joint corners of the mechanical arm, due to the collision of the tail end of the mechanical arm within very short time, an fitness optimizing function for mechanical arm tracks is constructed; step 3, a five-level polynomial is adopted to conduct fitting on mechanical arm paths, and the simulated annealing genetic algorithm is utilized to solve the optimal track so as to meet a better fitness function. According to a mechanical arm capturing task, under the circumstance of ensuring the minimum base disturbance and the constraint of all the joint corners, the simulated annealing genetic algorithm is utilized to solve the optimal solution, and the convergence rate and the solving accuracy are increased.

Description

technical field [0001] The invention relates to the field of space manipulators, in particular to a manipulator path planning method based on a simulated annealing genetic algorithm. Background technique [0002] Trajectory planning is an important direction of space robot research. In order to complete a given task, the joints and ends of the robotic arm need to run according to a certain trajectory. Due to the large dimension, it is difficult to adopt the trajectory optimization algorithm, and it often converges prematurely, or the search efficiency is extremely low when it is close to the optimum. Aiming at these problems, the present invention proposes a simulated annealing genetic algorithm to perform trajectory planning for a space six-degree-of-freedom manipulator. Contents of the invention [0003] The object of the present invention is to provide a method for path planning of a manipulator based on a simulated annealing genetic algorithm to solve the above probl...

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/1664
Inventor 袁建平李晨熹张博王铮方静徐杨魏锦源彭志旺
Owner NORTHWESTERN POLYTECHNICAL UNIV
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