An investigation into novel strategies for adaptive, intelligent and robust control of autonomous robots through the study of dynamic interactions bet

点击翻译按钮获取中文摘要

The specific aim of my PhD project is to develop novel strategies for adaptive, intelligent and robust control of autonomous robots through the study of dynamic interactions between robots and their harsh environments. Through these advanced control strategies, the problem of efficiently dealing with the dynamic interactions between autonomous robots and their environments may be solved. The novelty of the control strategies lies in its use of information from on-board robotic vision systems and multiple sensory devices, equipped for the purpose of intelligent task planning and object manipulation. These advanced control strategies will be developed together with other sensor-based control techniques, such as hybrid force-position control.In particular, this project aims to address the challenging issues associated with the underlying adaptive, intelligent and robust control strategies for dynamic interactions between autonomous robotic systems and the harsh environments in which they operate. The objectives of the project are therefore as follows:1. Development of advanced control and communication prototyping platform for autonomous robotic applications that will enable the investigation of adaptive, intelligent and robust control strategies for autonomous robots in harsh environments;2. Refinement of communication and sensing system to meet the stringent flexibility and reliability requirements needed for robust and adaptive robotic applications, including capabilities to monitor operational consistency and detect errors;3. Development of adaptive, intelligent and robust control strategies for autonomous robots in hash environments, with particular focus on solving the problems of uncertainty and impact effects;4. Implementation of the above control strategies on the developed control and communication platform to deliver a working system installed and running within a lab demonstration environment.