Shared factor fuzzy inference device applied to hexapod robot

Abstract

The invention belongs to the technical field of foot type robot teleoperation. The invention discloses a shared factor fuzzy inference device applied to a hexapod robot. The problem that instability is prone to occurring when a multi-pod robot executes a special task on a complex terrain is solved. The shared factor fuzzy inference device applied to the hexapod robot designs a two-dimensional teleoperation system capable of realizing cooperative control of shared characteristics on the basis of a speed-pose cooperative teleoperation system. The stability condition of the multi-pod robot is analyzed through a stability margin criterion, and a sharing factor alpha is generated through a fuzzy inference system to distribute control weights for the teleoperation subsystem; control errors and control requirements of the multi-pod robot are combined through a main end controller, and the control errors and the control requirements are fed back to an operator in a tactile guiding force mode.The method can effectively solve the problem that the multi-pod robot is prone to questioning under the rugged terrain, and the working pressure of an operator is reduced while the transparency of thesystem is guaranteed.

Description

technical field [0001] The invention belongs to the technical field of teleoperation of legged robots, and in particular relates to a shared factor fuzzy reasoner and an implementation method thereof for efficient and stable walking of a hexapod robot teleoperated by an operator under rough terrain. Background technique [0002] Because legged walking robots have stronger adaptability and passing ability than wheeled or tracked mobile robots when facing complex terrain, they have been widely used in disaster rescue, sea and air exploration, exploration and other fields. But what needs to be recognized is that although legged robots can replace humans in dangerous working environments, due to the unpredictable complexity of the work site, it is difficult to ensure that the robot can adapt to the complex and changeable by relying solely on the robot's own intelligent control algorithm. Task requirements under working conditions. In order to improve the stability of the robot ...

AI Technical Summary

Problems solved by technology

When the robot is on a rough ground, there will be a large difference between the robot's planned landing position and the actual position. Therefore, the hexapod robot may lose speed in the direction of the target movement, and the fluctuation of the body may cause the robot to lose speed. Insufficient stability margin. At this time, if this control framework is adopted, it is difficult to meet the demand for stability margin of the footed robot in rough terrain. During the operation, the robot is prone to instability or even tipping, resulting in loss of control, Drive system failure, component damage and other problems; using the multi-master single-slave (MMSS) control framework to coordinate the robot's travel speed and body pose can better control the travel tasks of the hexapod robot in rough terrain

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