ARTIGO TÉCNICO Pedro Queirós, Cristóvão Sousa, Rui Cortesão Institute of Systems and Robotics, University of Coimbra, Portugal pqueiros@isr.uc.pt, crisjss@gmail.com, cortesao@isr.uc.pt This work was partially supported by the Portuguese Science and Technology Foundation FCT project number PTDC/EEA-ACR/72253/2006 and by the FCT National Program for Scientific Re-Equipment, REEQ/1113/EEI/2005
ROBOTIC SETUP FOR MEDICAL APPLICATIONS ABSTRACT The paper presents a robotic setup for medical applications developed at the Institute of Systems and Robotics – University of Coimbra. Computed torque control, feedback linearization and operational space techniques are used to develop a telemanipulation system with haptic force feedback. The operational space control has a position-position teleoperation architecture with a haptic device in the loop. Based on position commands, the Cartesian dimensions are controlled by a decoupled plant powered by multiple Active Observers (AOBs), which provide model reference adaptive control. In addition, an active impedance control scheme for comanipulation tasks is described following the same decoupled control structure. The system devices as well as the involved communication protocols are discussed. Finally, the developed software architecture that integrates the different system components is presented. Keywords:Telemanipulation, haptics, telepresence, comanipulation robot, active observer, impedance.
I. INTRODUCTION The impact of robotic systems in surgery promises to be comparable to the manufacturing robots in industrial production. Surgical robots and robotic systems may be seen as “smart” surgical tools that enable surgeons to treat individual patients with improved efficacy, greater safety, and less morbidity then would be possible otherwise [1]. The goal of medical robotics is not to replace the physician by a robot, but to provide a new set of versatile tools to treat patients in a faster and better way. Surgical robots can be grouped into two main groups: 1) surgeon extenders, which are operated directly by the surgeon, augmenting and enhancing the ability to manipulate surgical instruments. Examples include the Intuitive Surgical DaVinci system [2], the Zeus system, the ROBODOC system for joint replacement surgery [3], [4] and the Accuracy Cyberknife for radio-surgery [5]. 2) auxiliary surgical tools [6]. In this group, robots generally work side-by-side with the surgeon and perform such functions as endoscope holding or retraction and automatic laparoscopic camera guidance [7]. These systems typically provide one or more direct control interfaces such as joysticks, head trackers or voice control. However, there have been some efforts to make these systems more autonomous to require less surgeon control. The paper describes a robotic setup for medical applications addressing telemanipulation and comanipulation paradigms. It is organized as follows. Sections II and III describe the experimental setup and the software architecture, respectively. Sections IV and V discuss telemanipulation and comanipulation, focusing in computed torque control techniques. Finally the conclusions are summarized in Section VI.
and is connected by a CAN bus to a PC (Intel® CoreTM 2 Duo at 2.13GHz) running RTAI Linux. For simulation purposes, the WAM® can be replaced by its simulator providing a noiseless and well defined environment for testing and development. A screenshot of the simulator is depicted in Fig. 1(c). The simulation takes into account the real robot dynamic and kinematic parameters, including: link size, mass and inertia parameters. Based in the
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II. EXPERIMENTAL SETUP Figure 1 shows the main components of the master and slave stations. The master station has a Phantom Desktop haptic device, with 6-DOF position/ orientation outputs and 3-DOF force inputs (see Fig. 1(a)). The slave station depicted in Fig. 1(b) has the WAM® medical robot, which is a lightweight anthropomorphic arm with 7 Degrees of Freedom (DOF). Since almost all joints are cable driven (only the last one has gears) the robot has almost zero backlash and is highly backdrivable. All of these characteristics make the WAM® an excellent platform for force control and human interaction applications. To measure the contact forces and moments, a JR3 force sensor is attached to the robot end-effector. The robot is joint-torque controlled
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c) Figure 1 . Master and slave stations. a) Phantom Desktop haptic device. b) Robot manipulator WAM® 7-DOF with a JR3 force sensor at the end-effector. c) WAM® simulator screenshot.
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Figure 4 . Overview of the telemanipulation architecture. Master and slave stations connected by virtual coupling.
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Figure 5 . Computed torque techniques. a) Feedback linearization. J is the Jacobian, h is the task space mass matrix and Ks is the environment stiffness. b) Force controller. K2 is an inner damping loop gain, La is the control loop gain and x^ is the state space estimation.
terms, respectively. o is the generalized joint torque which equals the sum of motor oc and external oe torques. This model is converted to the task space and linearized using a nonlinear feedback method, using also the JR3 force sensor information (Fe). The resulting system plant is a decoupled double integrator for each Cartesian dimension. A force controller runs on top of this plant powered by Active Observers (AOB) [9] (see Fig. 5). The control reference is the force from the Virtual Coupling block (Fd) and the measured output is the sensed force (Fe). The slave station exchanges signal data without external control, though. The reference forces, both for Phantom and robot, are generated through a virtual position coupling. This coupling is a simple gain over the positions displacement, Kv (Xp—Xe), which acts as a virtual spring. Positions can be scaled so that the movement of the robot is a scaled version of Phantom movements. Force feedback can also be differently scaled, enabling reduction or augmentation of contact force perception by the operator. This concept is called augmented reality.
V. COMANIPULATION CONTROL Another research field we are exploring is the comanipulation of medical robots. Comanipulation implies physical interaction between the robot and the human operator. Instead of moving a haptic device, the operator executes the task by grabbing the robot end-effector or its body. The robot can implement safe constrained zones, filter human commands, compensate tool/robot weights, or have a more active behavior like active guidance and active impedance [10], [11]. In this way, the surgeon is still in charge but with enhanced capabilities. In our work we are implementing an active impedance architecture for comanipulation to create virtual walls. This architecture uses a force controller similar to the telemanipulation one. The main differences are the reference force (Fd) which is set to zero, and the measured force (Fe) which is virtually calculated based on current and desired end-effector positions.
VI. CONCLUSIONS An overview of the medical robotics setup developed at the Institute of Systems and Robotics – University of Coimbra has been presented, focusing on devices, communications, software and control architectures. The main characteristics of the experimental setup have been introduced. A haptic
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device has been connected to the medical robot through Internet based protocols for telerobotic surgery, using a master slave architecture. The developed software architecture is focused on modularity at both device and control levels, enabling device integration without major software modifications. Advanced control techniques for telemanipulation and comanipulation have been presented, including dynamic modeling, feedback linearization, computed torque, state space control and stochastic estimation (e.g., AOB). Some complementary aspects like the medical environment and anatomy knowledge integration into the control architectures will be addressed in future work. Unlike industrial robotics, where control architectures are already settled, medical robotics has not yet a clear implementation path. Different tasks, with different environments, compliance, safety, telepresence and other issues, open a huge field for engineering research and development.
REFERENCES [1] T. Kanade, B. Davies, and C. N. Riviere, “Special issue on medical robotics,” Proceedings of the IEEE, vol. 94, no. 9, pp. 1649–1651, Sept. 2006. [2] G. Guthart and J. Salisbury, J.K., “The intuitiveTMtelesurgery system: overview and application,” Robotics and Automation, 2000. Proceedings. ICRA ’00. IEEE International Conference on, vol. 1, pp. 618–621 vol.1, 2000. [3] P. Kazanzides, B. Mittelstadt, B. Musits, W. Bargar, J. Zuhars, B. Williamson, P. Cain, and E. Carbone, “An integrated system for cementless hip replacement,” Engineering in Medicine and Biology Magazine, IEEE, vol. 14, no. 3, pp. 307–313, May/Jun 1995. [4] R. Taylor, H. Paul, B. Mittelstadt, W. Hanson, P. Kazanzides, J. Zuhars, E. Glassman, B. Musits, W. Williamson, and W. Bargar, “An image-directed robotic system for precise orthopaedic surgery,” Engineering in Medicine and Biology Society, 1990., Proceedings of the Twelfth Annual International Conference of the IEEE, pp. 1928–1930, Nov 1990. [5] (2008) Accuracy cyberknife. [Online]. Available: http://www.accuray.com/ [6] R. Taylor, “A perspective on medical robotics,” Proceedings of the IEEE, vol. 94, no. 9, pp. 1652–1664, Sept. 2006. [7] A. Casals, J. Amat, and E. Laporte, “Automatic guidance of an assistant robot in laparoscopic surgery,” Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on, vol. 1, pp. 895–900 vol.1, Apr 1996. [8] R. Cortesão, J. Park, and O. Khatib, “Real-time adaptive control for haptic telemanipulation with kalman active observers,” IEEE Transactions on Robotics, vol. 22, no. 5, pp. 987–999, Oct. 2006. [9] R. Cortesão, “On kalman active observers,” Int. J. of Intelligent and Robotic Systems, vol. 48, no. 2, pp. 131–155, Feb. 2007. [10] R. Cortesão, B. Zenowich, R. Araújo, and W. Townsend, “Robotic comanipulation with active impedance control,” in ASME-AFM World Conference on Innovative Virtual Reality, France, 2009, (in press). [11] G. Morel, “Applications of force feedback in medical and surgical robotics,” in Summer School on medical Robotics, France, 2005.
ROBOTIC SETUP FOR MEDICAL APPLICATIONS
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