Conference Paper

The plenhaptic guidance function for intuitive navigation in extended range telepresence scenarios.

Conference: IEEE World Haptics Conference, WHC 2011, 21-24 June 2011, Istanbul, Turkey
Source: DBLP
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    ABSTRACT: In the future, robots will have to assist human beings in the performance of several tasks. In order to achieve this goal, robots have to be able to follow human movement in a way that is transparent to the human operator. This paper presents a new method to make this cooperation more transparent. The method is based on an online variable impedance control using differentiation of the force as a natural sensor of human intention. This work will also demonstrate why velocity control should be used in the controller of a human-friendly robot rather than typical position control. The performance of the control scheme introduced here is also validated in an experimental cooperative drawing task involving a parallel manipulator and a human operator
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    ABSTRACT: Segmentation and recognition of operator-generated motions are commonly facilitated to provide appropriate assistance during task execution in teleoperative and human-machine collaborative settings. The assistance is usually provided in a virtual fixture framework where the level of compliance can be altered online, thus improving the performance in terms of execution time and overall precision. However, the fixtures are typically inflexible, resulting in a degraded performance in cases of unexpected obstacles or incorrect fixture models. In this paper, we present a method for online task tracking and propose the use of adaptive virtual fixtures that can cope with the above problems. Here, rather than executing a predefined plan, the operator has the ability to avoid unforeseen obstacles and deviate from the model. To allow this, the probability of following a certain trajectory (subtask) is estimated and used to automatically adjusts the compliance, thus providing the online decision of how to fixture the movement
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    ABSTRACT: This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the "artificial potential field" concept. In this approach, collision avoidance, traditionally considered a high level planning problem, can be effectively distributed between different levels of control, allowing real-time robot operations in a complex environment. We have applied this obstacle avoidance scheme to robot arm using a new approach to the general problem of real-time manipulator control. We reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation. This method has been implemented in the COSMOS system for a PUMA 560 robot. Using visual sensing, real-time collision avoidance demonstrations on moving obstacles have been performed.
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May 23, 2014