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Spatial double-arm system constraint motion planning method based on deep intensive learning

A technology that strengthens learning and constrains motion. It is applied in the direction of manipulators, program-controlled manipulators, and manufacturing tools. It can solve problems such as poor versatility and collision damage of manipulators.

Active Publication Date: 2021-01-05
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0004] Aiming at the deficiencies of the above-mentioned prior art, the purpose of the present invention is to provide a space dual-arm system constrained motion planning method based on deep reinforcement learning to solve the problem of poor versatility of traditional motion planning methods in the prior art and unconstrained based Problems such as collision damage of the robotic arm caused by the motion planning method of the deep reinforcement learning algorithm

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  • Spatial double-arm system constraint motion planning method based on deep intensive learning
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  • Spatial double-arm system constraint motion planning method based on deep intensive learning

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Embodiment Construction

[0059] In order to facilitate the understanding of those skilled in the art, the present invention will be further described below in conjunction with the embodiments and accompanying drawings, and the contents mentioned in the embodiments are not intended to limit the present invention.

[0060] refer to figure 1 As shown, a method for constrained motion planning of a space dual-arm system based on deep reinforcement learning of the present invention, the steps are as follows:

[0061] 1) Using the generalized Jacobian matrix to establish the kinematics model of the dual-manipulator system in free-floating space;

[0062] The kinematics model of the space dual manipulator system is established according to the following formula (1):

[0063]

[0064] in, I v 0 and I ω 0 are the velocity vector and angular velocity vector of the space manipulator base in the inertial reference system, respectively; and are the velocity vector and angular velocity vector of the firs...

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Abstract

The invention discloses a spatial double-arm system constraint motion planning method based on deep intensive learning. The method comprises the following steps of 1) establishing a kinematic model ofa free floating spatial double-mechanical-arm system by utilizing a generalized jacobian matrix; 2) designing a spatial double-arm system motion planning algorithm based on the kinematic model of thespatial double-arm system in combination with a DDPG algorithm; and 3) designing a reward function in the DDPG algorithm to realize the satisfaction of each constraint condition in the spatial double-arm system motion planning algorithm, including speed constraint of a mechanical arm end effector and self-collision constraint of double-mechanical-arm cooperative motion. The universality and safety of the motion planning algorithm is improved.

Description

technical field [0001] The invention belongs to the technical field of motion planning of a space manipulator, and in particular relates to a constrained motion planning method for a space dual-arm system based on deep reinforcement learning. Background technique [0002] As a very effective executive mechanism in space manipulation tasks, the space manipulator has high engineering application value in space manipulation tasks such as repairing faulty satellites, removing space debris, and assembling large space structures. Due to the influence of the microgravity environment in space, there are obvious differences in the motion characteristics of the space manipulator and the ground manipulator. Specifically, the ground manipulator generally has a fixed base, while the space manipulator generally has a fixed base while the space manipulator performs tasks. are in a free-floating state. Compared with the space single-arm system, the space dual-arm system is safer and more r...

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/1607B25J9/1615B25J9/1664
Inventor 李爽李胤慷佘宇琛
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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