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Title: Vision-based trajectory control of unsensored robots to increase functionality, without robot hardware modification
Author: Ortenzi, Valerio
ISNI:       0000 0004 6346 6588
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2017
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In nuclear decommissioning operations, very rugged remote manipulators are used, which lack proprioceptive joint angle sensors. Hence these machines are simply tele-operated, where a human operator controls each joint of the robot individually using a teach pendant or a set of switches. Moreover, decommissioning tasks often involve forceful interactions between the environment and powerful tools at the robot's end-effector. Such interactions can result in complex dynamics, large torques at the robot's joints, and can also lead to erratic movements of a mobile manipulator's base frame with respect to the task space. This Thesis seeks to address these problems by, firstly, showing how the configuration of such robots can be tracked in real-time by a vision system and fed back into a trajectory control scheme. Secondly, the Thesis investigates the dynamics of robot-environment contacts, and proposes several control schemes for detecting, coping with, and also exploiting such contacts. Several contributions are advanced in this Thesis. Specifically a control framework is presented which exploits the constraints arising at contact points to effectively reduce commanded torques to perform tasks; methods are advanced to estimate the constraints arising from contacts in a number of situations, using only kinematic quantities; a framework is proposed to estimate the configuration of a manipulator using a single monocular camera; and finally, a general control framework is described which uses all of the above contributions to servo a manipulator. The results of a number of experiments are presented which demonstrate the feasibility of the proposed methods.
Supervisor: Not available Sponsor: UK Nuclear Decommissioning Authority
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TJ Mechanical engineering and machinery ; TK Electrical engineering. Electronics Nuclear engineering