Study Of Robot Master-slave Control Algorithm Incorporating Force Perception

With the rapid development of science and technology,the pace of human exploration in the fields of electrically powered operations,space exploration,and telemedicine is accelerating day by day.However,the high risk,complexity and uncertainty of the operating environment not only pose a threat to personal safety,but also make it difficult for fully autonomous intelligent robots to meet the demand for real-time operation and accuracy due to the development of artificial intelligence and sensor technology.Therefore,it is important to build a robot master-slave control system that incorporates advanced human decision-making awareness and multiple sensory feedback information to enhance robot operations and reduce the burden and safety risks of operators.The kinematic modeling of the master force feedback device Geomagic Touch and the slave UR5 robot arm is completed and simulated for the operational requirements of the robot master-slave control system.On this basis,the robot master-slave mapping strategy is proposed,in which the incremental mapping method is used for position control and the absolute mapping method is used for attitude control,laying the foundation for the subsequent experimental development and verification of the master-slave motion control algorithm and the force sensing algorithm.This paper proposes an improved RRT~* algorithm(GPF-RRT~*)based on the adaptive variable step size of Gaussian potential field to address the shortcomings of the path planning algorithm in the unstructured environment,and lays the foundation for the subsequent proposed path interaction force sensing algorithm.The analysis proves that the improved algorithm has strong stability in unstructured environment.For the influence of external interference on the master-slave control algorithm,this paper proposes a force sensing algorithm based on virtual fixture and virtual impedance.Firstly,the modeling of dynamics is completed by using Lagrangian method.Secondly,the guided virtual fixture and the forbidden virtual fixture are constructed based on the path information and the environment information,respectively.Then,the virtual impedance model is constructed at the end of the master-slave robot,and the error force compensation is used to constrain and regulate the operator’s behavior.Finally,the analysis of the force-aware algorithm is completed on the experimental platform,and the results show that the force-aware algorithm can effectively improve the efficiency and accuracy of master-slave control.