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构建机器人单元和机器人教学新任务方面做出重大努力。由此产生的高工程成本阻止了机器人成为多功能可重新编程的机器，快速适应新任务。该研究计划的“长期”目标是开发使用图像伺服（“IS”）的高性能控制方法，以实现机器人在非结构化环境中的操作。尽管IS具有巨大的潜力，但缺乏鲁棒性阻碍了IS集成到许多现实世界的应用中。 此外，以前的工作主要集中在视觉伺服，留下了许多与其他成像传感器的集成相关的问题没有解决。该提案的短期目标集中在使用图像反馈的“鲁棒”控制技术的发展的未解决的问题。 除视觉传感器外，重点将放在超声/回波、计算机断层扫描和荧光透视的图像上。拟议的研究的主要特点包括：i）一个强大的功能演示计划在IS背景下的发展; ii）第一个全面的IS回路不确定性模型，将用于设计一个新的混合框架，强大的多机制运动规划和控制技术的发展;和iii）扩展的结果，以解决困难的定位问题，在新的应用程序，如连续体机器人的控制。所提出的研究结果可以消除单元结构和机器人教学工作，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。这项研究工作的成果，预计将需要独特的和系统的程序设计的强大的操纵系统。这些程序的可用性可以通过改善当前任务的执行和促进以前被认为几乎不可能使用经典技术的应用程序来产生重大和直接的影响。此外，这项研究将产生新的编程范式的基础，其中的目标将被指定在集成的任务和图像空间。

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.