Formation transformation method for multi-robot system based on multi-motion modal and multi-viewpoint geometry

Abstract

The invention discloses a multi-robot system formation transformation method based on multi-motion mode and multi-viewpoint geometry, which includes: calculating the geometric tensor of mutual projection of the target formation multi-robot system; calculating the geometric tensor at each moment, and Compare the above geometric tensors. If they are the same, it means that the formation transformation is completed. If they are not the same, select one follower machine and mark it as C1, and the two lead machines as C2 and C3, and calculate the two focus tensors between C1, C2, and C3. The two projected straight lines of the quantity and the target position of C1 on the image, the intersection point of the two projected straight lines is the projected point x of the target position of C1 on the image; let C1 move along the line connecting the initial position and x until C1 is at C2, The position of the projection point on the C3 camera image coincides with the projection position after formation transformation, and the above-mentioned processing is performed on the remaining followers one by one, thus completing the formation transformation of the multi-robot system. The method provided by the invention enables the system to have a high-precision formation transformation function in complex field environments.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to a multi-robot system formation transformation method based on multi-motion mode and multi-viewpoint geometry. Background technique [0002] Robotics is a compound system discipline involving sensing, mechanical transmission, computer science, cognitive social science and other fields. In the fields of military, national defense, security, industry, transportation, etc., mobile robots perform various tasks instead of humans, and their advantages in efficiency and safety are also reflected. Among them, multiple robots with relatively simple structures and sensing means cooperate to complete a complex task, which increases safety while reducing the cost of the robot mechanism. For example, in a dangerous environment, robots cooperate to perform transportation tasks, which can avoid various injuries caused by the dangerous environment to personnel. Therefore, people consider that a ...

AI Technical Summary

Problems solved by technology

However, in the face of complex field environments, the existing multi-robot control technology requires a unified queue representation framework, which has poor formation transformation ability and weak applicability during movement.

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