A robot system generally has several degrees of freedom of motions as well as different kinds of sensors. Basic behaviors are planned based on these sensors' feedback. We take advantage of the Jacobian matrix to d...
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A robot system generally has several degrees of freedom of motions as well as different kinds of sensors. Basic behaviors are planned based on these sensors' feedback. We take advantage of the Jacobian matrix to describe the differential relations between the sensor feedback and the motor motions. Hence, the relation between two sensors could be formulated by the two respective Jacobian matrices of both sensors to motors. Multisensor integration can, thus, be employed for better performance of the robot system. Experiments of basic behavior acquisition like gazing and posture control of a robot head are conducted. The performances of the two basic behaviors before and after multisensor integration are compared, which demonstrate the performance and robustness of the proposed multisensor integration method. (C) Koninklijke Brill NV, Leiden and The robotics Society of Japan, 2009
A Simulation, Animation, Visualization and Interactive Control (SAVIC) environment has been developed for the design and operation of an integrated robotic manipulator system. This unique system possesses the abilitie...
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A Simulation, Animation, Visualization and Interactive Control (SAVIC) environment has been developed for the design and operation of an integrated robotic manipulator system. This unique system possesses the abilities for (1) multi-sensor simulation, (2) kinematics and locomotion animation, (3) dynamic motion and manipulation animation, (4) transformation between real and virtual modes within the same graphics system, (5) ease in exchanging software modules and hardware devices between real and virtual world operations, and (6) interfacing with a real robotic system. This research is focused on enhancing the overall productivity of an integrated human-robot system. This paper describes a working system and illustrates the concepts by presenting the simulation, animation and control methodologies for a unique mobile robot with articulated tracks, a manipulator, and sensory modules.
In this paper we show how large efficiencies can be achieved in model-based 3-D vision by combining the notions of discrete relaxation and bipartite matching. The computational approach we present is empirically inter...
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In this paper we show how large efficiencies can be achieved in model-based 3-D vision by combining the notions of discrete relaxation and bipartite matching. The computational approach we present is empirically interesting and capable of pruning large segments of search space-an indispensable step when the number of objects in the model library is large and when recognition of complex objects with a large number of surfaces is called for. We use bipartite matching for quick wholesale rejection of inapplicable models. We also use bipartite matching for implementing one of the key steps of discrete relaxation: the determination of compatibility of a scene surface with a potential model surface taking into account relational considerations. While we are able to provide the time complexity function associated with those aspects of the procedure that are implemented via bipartite matching, we are not able to do so for the interative elements of the discrete relaxation computations. In defense of our claim regarding computational efficiencies of the method presented here, all we can say is that our algorithms do not take more than a couple of iterations even for objects with more than 30 surfaces.
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