Intelligent Haptic Controls for Robotic Teleoperation

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Computer automation of tasks often implements "control systems", like a car's cruise-control that keeps the speed constant by controlling the throttle. A simple feedback control decides on the control input by multiplying the output error by a negative constant; in the case of the cruise control the throttle control is proportional to the error in speed. More accurate feedback control laws are normally achieved by performing more complex mathematical operations on the error signal, especially integration and differentiation. On the other hand, my research focuses on improving control systems through biologically inspired methods, specifically by utilizing the Cerebellar Model Arithmetic Computer or CMAC, a computer algorithm modelled on the cerebellum in the human brain. Such "artificial neural networks" incorporate a learning and memorization aspect into the control, resulting in adaptation to unknown variables (like the weight of the passengers in the car in the cruise control example). In this proposal, I will apply the CMAC to the new and exciting area of robotic "haptics" - the control of robotic manipulator arms through hand controllers that let people feel and/or command the forces. Applications range from the Canadarm2/Dextre to submarine manipulators to surgical robots. Most hand-controlled robotic systems only let people control movement (position or speed) while relying strictly on their eyes to know what the robot is doing. Some contemporary robotic systems now let people control the robot while also feeling the forces encountered by the robot; the sense of touch provides a more intuitive interaction resulting in faster and more accurate manipulation. Current control system technology, using mathematical feedback laws, may not produce a satisfactory feel to the user under certain conditions, like when there are time-delays in the system or the environment changes suddenly. Consider a surgical robot, which ideally should be able to move outside the patient, perform surgical tasks with human tissue, and push against bone (and transition between these tasks) without difficulty even when the surgeon does not feel the forces at exactly the same time as the robot. With current technology, surgical robots with haptics are designed for one particular type of task and can do another only with great difficulty, or not at all. Particular problems that can be encountered include sharp abrupt movements, unwanted vibrations, excessive movement during punctures, and excessive forces during collisions. I will use the CMAC to improve the control systems, so that the robot will naturally adapt its motions/forces to different environments while, at the same time, reacting more like a person would. By relying more on the CMAC's memorization capabilities rather than only on measurements of error, the motions can be made much smoother with less, or no, vibrations. It also becomes possible to smoothly switch between two different CMAC controls, so that during puncture or collision a smooth transition can be made between appropriate controls - avoiding extreme movement or forces. It is of utmost importance that the CMAC controls be developed within a mathematical framework that guarantees stability in the presence of the small unavoidable time delays. Because people will experience the system as more intuitive, they will require less formal training beforehand and experience less stress when controlling the system. Project NeuroArm at Foothills Hospital in Calgary has opened their haptics lab to me, which will give me the opportunity for testing and evaluating my controls using the latest in haptic equipment in close consultation with surgeons who use such systems on a daily basis.