A robust polynomial-time algorithm for model-based pose estimation from tactile grasp data is presented. A minimal representation criterion is used to formulate the matching problem as a global optimization. The hypot...
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A robust polynomial-time algorithm for model-based pose estimation from tactile grasp data is presented. A minimal representation criterion is used to formulate the matching problem as a global optimization. The hypothesize-and-test paradigm is invoked to search for the optimal solution. A three-on-three match of model features to data features is used to reduce the transform search space to polynomial size. A polynomial-time assignment algorithm is used to compute the optimal correspondence for each hypothesized pose. The strength of the algorithm lies in its ability to perform with noisy or incomplete data and with missing or spurious features. It is capable of rejecting outliers and finding partial matches, and it produces sensible results even in the presence of large noise. The algorithm has been implemented and tested on actual data.< >
When the uncertainty is large compared to clearances between objects, some form of compliance is required for a robot to manipulate these objects. Such situations include, but are not restricted to, assembly operation...
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When the uncertainty is large compared to clearances between objects, some form of compliance is required for a robot to manipulate these objects. Such situations include, but are not restricted to, assembly operations. Compliance can be thought of as a task-dependent mapping from sensed forces to corrective motions which bring the robot closer to its goal. A methodology for the automated synthesis of this mapping is described. The possible erroneous configurations of the robot together with their resulting contact forces are computed, and a corrective motion is identified for each configuration. The validity of the mapping is checked to ensure that the sensed forces will provide unambiguous information during the actual execution of the planned compliant motion.< >
In this paper, active control of flexible structures through utilization of structure mounted sensors and actuators is considered. Specifically, dynamic feedback design utilizing signals from the accelerometer mounted...
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In this paper, active control of flexible structures through utilization of structure mounted sensors and actuators is considered. Specifically, dynamic feedback design utilizing signals from the accelerometer mounted on the structure is discussed. Furthermore, utilization of piezoceramics for sensing and actuation to provide a higher level of control for vibration damping is investigated. The flexible pointing system considered here is the test-bed at the Army Research Development engineering Center (ARDEC), which is a scaled-down representation of real-life targetting systems. This setup is also a nice benchmark problem for system identification and different control design philosophies. The approaches advocated here are based on Youla's parametrization of stabilizing controllers, Wiener-Hopf design and decentralized frequency shaping. Modelling aspects for the setup, taking all the structural intricacies into account, are discussed. The preliminary results indicate a significant improvement in performance through utilization of these control schemes.
There is no standard representation scheme that is followed by different groups of robot designers to describe the orientation of a rotating rigid body. For a sensor-based robot, the particular rotation representation...
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There is no standard representation scheme that is followed by different groups of robot designers to describe the orientation of a rotating rigid body. For a sensor-based robot, the particular rotation representation scheme used by the robot affects not only the specification of the positioning of the arm and end-effector, but also the specification of the placement of the sensors and the method of computing the sensory-to-world transformation. Thus the need for finding the transformation between different rotation representations is obvious for one involved in the development of high-level software systems that need to be transported to different robots utilizing different rotation representation schemes. Among those representation schemes, Euler angle representations are widely used in commercial robots as well as in research laboratory robots. Typically, there are three different Euler angle representation systems, and each system describes a particular orientation of a rigid body in a reference coordinate frame by specifying three angles. Mathematical derivations of the transformation relationships underlying the parameters from two most commonly utilized representation schemes are presented. These relationships are derived in two different ways. One is based upon the solution of the inverse transform for Euler angles and the other is based upon the Napier's rules associated with spherical trigonometry.
This paper presents an approach for designing robust tracking controller for lumped mass model of a vibrating link (VL) robot manipulator. The control methodology is intuitively simple since it is based on concepts wh...
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Knowledge of the distance between a robot and its surrounding environment is vital for any robotic system. The robot must obtain this information rapidly in order to plan and react in real-time. Our technique first su...
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A computational framework for an accurate, robust, and efficient stereo approach is developed. Most of the deficiencies prevailing in current computational models of stereo can be attributed to their use of a single, ...
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In this paper we nzake an attempt to bring out the rationale that, for complex robotic applications, contact sensors can provide certain vital information quite easily as compared to non-contact sensors. We begin with...
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Intelligent robots interact with the real world by employing their advanced sensory mechanisms to perceive their environment, and their effectors and tools to change the state of their environment. Such intelligent ro...
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A two-layer continuous-time cellular neural network for finding the Radon transform of a binary image is presented. The functionality of this cellular neural network follows from the functionality of the connected com...
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A two-layer continuous-time cellular neural network for finding the Radon transform of a binary image is presented. The functionality of this cellular neural network follows from the functionality of the connected component detector cellular neural network.
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