Robust Image-Servo Control of Robotic Manipulators for Unstructured Environments

尽管在机器人控制方面取得了重大进展，但机器人定位问题仍然需要在机器人单元的结构和机器人新任务的教学方面付出巨大努力。由此产生的高工程成本阻碍了机器人成为多用途的可重新编程机器，无法快速适应新任务。该研究计划的“长期”目标是利用图像伺服（“is”）开发高性能控制方法，使机器人能够在非结构化环境中操作。尽管IS具有巨大的潜力，但缺乏鲁棒性阻碍了将IS集成到许多实际应用中。此外，以前的工作主要集中在视觉伺服上，留下了许多与其他成像传感器集成相关的问题尚未解决。本提案的短期目标集中在使用图像反馈开发“鲁棒”控制技术的未解决问题上。除了视觉传感器外，重点将放在超声/回波，计算机断层扫描和透视的图像上。提出的研究的关键特征包括：i)在IS环境中开发一个健壮的特征表示方案；ii)开发第一个全面的IS回路不确定性模型，该模型将用于设计一种新的混合框架，用于鲁棒多状态运动规划和控制技术；iii)将结果扩展到解决新应用中的定位难题，如连续体机器人的控制。提出的研究结果可以消除细胞结构和机器人教学的努力，并将提供放松机器人机构的机械精度和刚度要求的潜力，降低其成本并扩展其应用范围。这项研究工作的结果预计需要独特的和系统的程序设计稳健的操作系统。这些程序的可用性可以通过改进当前任务的执行，并通过促进以前用经典技术几乎不可能实现的应用，从而产生重大而直接的影响。此外，本研究将产生新的编程范式的基础，其中目标将在集成任务和图像空间中指定。

Despite significant advances in robot control, robot positioning problem still requires significant effort in structuring the robotic cells and robot teaching for new tasks. The resulting high engineering costs prevent robots from being versatile reprogrammable machines, adapting quickly to new tasks. The "long-term" objective of this research program is on the development of high-performance control methods using image servoing ("IS"), to enable robot operations in unstructured environments. Despite enormous potential of IS, lack of robustness has hindered the integration of IS into many real-world applications. Also the previous work has mainly focused on visual servoing, leaving many issues related to the integration of other imaging sensors unsolved. The short-term objectives of this proposal focus on the unresolved issues for the development of "robust" control techniques using image feedback. In addition to vision sensor, the focus will be on the images from ultrasound/echo, computed tomography, and fluoroscopy. Key features of the proposed research include: i) development of a robust feature presentation scheme in the IS context; ii) development of the first comprehensive IS loop uncertainty model that will be used to design a novel hybrid framework for robust multi-regime motion planning and control techniques; and iii) extending the results to solve difficult positioning problems in new applications such as the control of continuum robots. The proposed research results could eliminate cell structuring and robot teaching efforts, and would provide the potential to relax the mechanical accuracy and stiffness requirements for robotic mechanisms, reducing their cost and extending their applications. The outcome of this research work is expected to entail unique and systematic procedures for the design of robust manipulation systems. The availability of such procedures could have a significant and immediate impact by improving the execution of current tasks and by facilitating applications previously taught to be almost impossible with classical techniques. Also, this research will yield to the foundation of new programming paradigm, in which the goals will be specified in integrated task and image spaces.