Summary.Haptic virtual fixtures are software-generated force and position signals applied to human operators in order to improve the safety, accuracy, and speed of robot-assisted manipulation tasks. Virtual fixtures are effective and intuitive because they capitalize on both the accuracy of robotic systems and the intelligence of human operators. In this paper, we discuss the design, analysis, and implementation of two categories of virtual fixtures: guidance virtual fixtures, which assist the user in moving the manipulator along desired paths or surfaces in the workspace, and forbidden-region virtual fixtures, which prevent the manipulator from entering into forbidden regions of the workspace. Virtual fixtures are analyzed in the context of both cooperative manipulation and telemanipulation systems, considering issues related to stability, passivity, human modeling, and applications.

This work focuses on the implementation of a vision-based motion guidance method, called virtual fixtures, on admittance-controlled human-machine cooperative robots with compliance. The robot compliance here refers to the structural elastic deformation of the device. The system uses computer vision as a sensor for providing a reference trajectory, and the virtual fixture control algorithm then provides haptic feedback to implemented direct, shared manipulation. It then discusses experiments to evaluate both speed and accuracy of the proposed constraints on human speed and accuracy versus free motion in a steady-hand paradigm. The result indicates improvements in the performance of human in the desired task execution.

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, which describes a framework for task level control on the Steady Hand Robot at JHU and which reports demonstrations of several representative tasks, including retinal cannulation, on dry lab and ex-vivo phantoms. The Publisher also refers to Figure 5 of the Article and wishes to reference the depiction of retinal cannulation in Dr. Kumar's thesis, which reflects a task sequence that was performed for Dr. Kumar's thesis and is depicted in the thesis as Figure 5.13.

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Abstract-Since its inception about three decades ago, modern minimally invasive surgery has made huge advances in both technique and technology. However, the minimally invasive surgeon is still faced with daunting challenges in terms of visualization and hand-eye coordination.At the Center for Computer Integrated Surgical Systems and Technology (CISST) we have been developing a set of techniques for assisting surgeons in navigating and manipulating the three-dimensional space within the human body. In order to develop such systems, a variety of challenging visual tracking, reconstruction and registration problems must be solved. In addition, this information must be tied to methods for assistance that improve surgical accuracy and reliability but allow the surgeon to retain ultimate control of the procedure and do not prolong time in the operating room.In this article, we present two problem areas, eye microsurgery and thoracic minimally invasive surgery, where computational vision can play a role. We then describe methods we have developed to process video images for relevant geometric information, and related control algorithms for providing interactive assistance. Finally, we present results from implemented systems.

Real-time image overlay significantly enhances controlled puncture during needle insertion. Force feedback may not be necessary except in circumstances where visual feedback is limited.

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