Dynamic fuzzy force field based force-feedback for collision avoidance in robot manipulators

Advanced remote teleoperation of robot manipulators enable complex tasks to be performed in hostile or inaccessible environments, without the physical presence of a human. For increased effectiveness of teleoperation, maintaining accuracy and speed of task while minimizing collisions is important. Visual and auditory inputs to the user aid in accurate control. However, to further increase the speed and accuracy, tactile and kinesthetic force-feedback information can be used. One of the most common methods of force-feedback generation is the virtual force field based method. However, in complex environments where increased accuracy is required, static force field based methods are insufficient. This paper presents a dynamically varying, virtual force field based force-feedback generation method for obstacle avoidance in remotely operated robot manipulators. The presented method utilizes a fuzzy logic model to dynamically vary a virtual force field surrounding the manipulator in real-time. The fuzzy controller utilizes the distance vectors to obstacles and the velocity vectors of the manipulator components to generate the force field in each axis. The generated force field is then used to calculate the final force-feedback that is sent to the user. The presented method was implemented on a simple 3-DOF robot manipulator, and compared to a typical static force field based force-feedback generation method. Test results show that the task completion time is significantly improved without significant loss of accuracy in certain tasks when the presented force-feedback method is used.