Hexapod robot obstacle avoidance method based on fuzzy Q learning

A hexapod robot and robot technology, applied in two-dimensional position/channel control and other directions, can solve the problem that obstacle avoidance algorithms cannot be applied to hexapod robots, and achieve the effect of ensuring accuracy

Inactive Publication Date: 2018-01-09
NANJING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is that the existing obstacle avoidance algorithm cannot be applied to the situation of a hexapod robot operating in a complex working environment

Method used

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  • Hexapod robot obstacle avoidance method based on fuzzy Q learning
  • Hexapod robot obstacle avoidance method based on fuzzy Q learning
  • Hexapod robot obstacle avoidance method based on fuzzy Q learning

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Embodiment Construction

[0030] The fuzzy Q-learning-based hexapod robot obstacle avoidance method disclosed in the present invention is a fuzzy Q-learning-based hexapod robot obstacle avoidance system, which includes a distance measurement system, a fuzzy control system and a hexapod robot motion system.

[0031] Among them, the distance measurement system is mainly composed of 9 ultrasonic sensors installed in front of the hexapod robot; the fuzzy control system is mainly composed of modules such as membership function and fuzzy reasoning; the motion system of the hexapod robot is mainly composed of the CR-6 robot model and the main control system. device composition.

[0032] When the system is working, firstly, the obstacle information of the hexapod robot is obtained with the help of ultrasonic sensors, and the measurement results are fuzzified by the distance membership function, and the obstacle information is converted into a limited state set; then the hexapod is built in Matlab software. The...

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Abstract

The invention provides a hexapod robot obstacle avoidance method based on fuzzy Q learning. The method comprises the steps that a hexapod robot measures the obstacle distance around the robot througha front ultrasonic sensor and converts the measured obstacle distance into a finite state set through fuzzy inference; according to the finite state set, obstacle avoidance simulation modeling is carried out in a simulation platform; a Q learning algorithm is used to learn the action taken by the hexapod robot in the corresponding state; the state set of the hexapod robot in the current state is determined; fuzzy inference is used to determine the action set of the hexapod robot; and the actions are fused to determine the next action. The obstacle avoidance method can realize a great obstacleavoidance effect in an environment where the number of obstacles is large, and has a good market prospect.

Description

technical field [0001] The invention relates to a robot obstacle avoidance method, in particular to a hexapod robot obstacle avoidance method based on fuzzy Q learning. Background technique [0002] The hexapod robot has multiple redundant degrees of freedom in structure, so it has high adaptability to the terrain environment. Hexapod robots can walk and overcome obstacles in the field with complex road conditions, and complete transportation operations in non-structural environments that cannot be completed by wheeled or crawler types. Exploration, planetary exploration and other fields have very broad application prospects. Therefore, the related research of hexapod robots has always attracted the attention of experts and scholars from all over the world, but how to improve the mobility of hexapod robots in unstructured environments is still an unsolved topic. [0003] The traditional hexapod walking movement adopts the method of fixed gait, such as three-legged gait, qu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 陈春林唐开强洪俊王岚吴涛于跃文陈文玉朱张青辛博刘力锋王子辉
Owner NANJING UNIV
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