Robot tail end contact positioning method based on deep learning

• Main Authors: LIANG ZHUO, LIN HAOYU, WEI DONGBO, QUAN PENGKUN, DI SHICHUN
• Format: Patent
• Language: Chinese; English
• Published: 13.01.2023
• Subjects: CALCULATING; CHAMBERS PROVIDED WITH MANIPULATION DEVICES; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HAND TOOLS; MANIPULATORS; PERFORMING OPERATIONS; PHYSICS; PORTABLE POWER-DRIVEN TOOLS; TRANSPORTING

The invention discloses a robot tail end contact positioning method based on deep learning, and belongs to the technical field of robot contact positioning. The method aims at solving the problems that in a robot tail end contact positioning method, a contact force bearing structure and a sensor are integrally designed, the sensor is prone to being damaged, and then the contact positioning accuracy is affected. Comprising the steps that an elastic compensator and an inertial sensor module are installed on a shaft clamping mechanism in a rigid separation mode; a contact template is designed, so that the shaft clamping mechanism drives the shaft to make contact with the position points and the center points on the contact template one by one; vibration generated by the elastic compensator is collected by the inertial sensor module; training a template positioning network formed by a long-short term memory neural network, a multi-layer convolutional neural network, a full-connection network and a softmax activat