138 resultados para Sensing for robot manipulation
Resumo:
A closed-loop control technique based on monitoring phase current risetime for switched reluctance (SR) motors without direct rotor-position sensors has been studied and implemented successfully. In this technique the variation in incremental phase inductance in a SR motor is used to detect rotor position. A control circuit for current-waveform-based rotor position detection has been implemented using hard-wire digital circuits. Torque-speed and system-efficiency characteristics resulting from the application of the method to a 4-kW, four-phase SR motor with an IGBT drive are presented.
Resumo:
This paper describes work on radio over fiber distributed antenna systems for improving the quality of radio coverage for in-building applications. The DAS network has also been shown to provide improved detection for Gen 2 UHF RFID tags. Using pre-distortion to reduce the problem of the RFID second harmonic, a simple heterogeneous sensing and communications system is demonstrated. © 2011 NOrthumbria University.
Resumo:
Skillful tool use requires knowledge of the dynamic properties of tools in order to specify the mapping between applied force and tool motion. Importantly, this mapping depends on the orientation of the tool in the hand. Here we investigate the representation of dynamics during skillful manipulation of a tool that can be grasped at different orientations. We ask whether the motor system uses a single general representation of dynamics for all grasp contexts or whether it uses multiple grasp-specific representations. Using a novel robotic interface, subjects rotated a virtual tool whose orientation relative to the hand could be varied. Subjects could immediately anticipate the force direction for each orientation of the tool based on its visual geometry, and, with experience, they learned to parameterize the force magnitude. Surprisingly, this parameterization of force magnitude showed limited generalization when the orientation of the tool changed. Had subjects parameterized a single general representation, full generalization would be expected. Thus, our results suggest that object dynamics are captured by multiple representations, each of which encodes the mapping associated with a specific grasp context. We suggest that the concept of grasp-specific representations may provide a unifying framework for interpreting previous results related to dynamics learning.