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

我的博士项目的具体目标是通过研究机器人与其恶劣环境之间的动态相互作用，为自主机器人的自适应、智能和鲁棒控制开发新的策略。通过这些先进的控制策略，可以有效地处理自主机器人与其环境之间的动态交互问题。该控制策略的新颖之处在于它利用了车载机器人视觉系统和多感官设备的信息，为智能任务规划和目标操纵而装备。这些先进的控制策略将与其他基于传感器的控制技术一起开发，例如混合力-位置控制。特别是，该项目旨在解决与自主机器人系统与其运行的恶劣环境之间动态交互的潜在自适应，智能和鲁棒控制策略相关的具有挑战性的问题。因此，该项目的目标如下：为自主机器人应用开发先进的控制和通信原型平台，这将使研究在恶劣环境下的自主机器人的自适应、智能和鲁棒控制策略成为可能；2 .改进通信和传感系统，以满足鲁棒性和自适应机器人应用所需的严格灵活性和可靠性要求，包括监控操作一致性和检测错误的能力；3 .开发哈希环境下自主机器人的自适应、智能和鲁棒控制策略，重点解决不确定性和冲击效应问题；在开发的控制和通信平台上实现上述控制策略，以提供在实验室演示环境中安装和运行的工作系统。

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.