Man-machine collaborative path planning method for mobile robot in unstructured environment

Abstract

The invention provides a man-machine collaborative path planning method for a mobile robot in an unstructured environment. The man-machine collaborative path planning method comprises the following steps: S1, enabling an operator to guide a path planner; s2 using a robot autonomous path planner; s3, performing hybrid filtering on the path planned by the operator obtained in the step S1 and the path autonomously planned by the robot obtained in the step S2, and synthesizing the path modified by the operator and the path autonomously planned by the robot; and S4, tactile feedback: feeding back the position deviation and the speed deviation of the planned path and the actual driving path of the robot to a handle of an operator in a force / tactile form. According to the method, the remote control technology based on force / touch and the autonomous planning technology are combined together, the defect that the mobile robot cannot autonomously complete field complex environment planning is overcome, the control burden of an operator is relieved, and the working efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of path planning and remote manipulation, in particular to a human-machine cooperative path planning method in an unstructured environment of a mobile robot. Background technique [0002] Although the intelligence level of mobile robot systems has made great progress, due to the limitations of their cognitive capabilities, autonomous planning problems in unstructured and other challenging environments cannot be completely handed over to robot systems. For example, for search and rescue work in unstructured environments such as after disasters, on the one hand, the disaster environment is too dangerous or humans cannot enter at all, and the scene is too complicated for autonomous robots to work autonomously. important. On the other hand, driving a robot in a disaster scene is a highly stressful and difficult job for the operator. A large part of the operator's work is just low-level tasks such as manipulatin...

AI Technical Summary

Problems solved by technology

[0002] Although the intelligence level of the mobile robot system has made great progress, due to the limitations of its cognitive ability, the autonomous planning problem in unstructured and other challenging environments cannot be completely handed over to the robot system.

For example, for search and rescue work in unstructured environments such as after disasters, on the one hand, the disaster environment is too dangerous or humans cannot enter at all, and the scene is too complex for autonomous robots to work autonomously. important

On the other hand, driving a robot in a disaster scene is a highly stressful and difficult job for the operator. A large part of the operator's work is just low-level tasks such as manipulating the robot and avoiding obstacles, while covering the search area and successfully finding Decreased performance in victims, etc.

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