Reliability maps for probabilistic guarantees of task motion for robotic manipulators

There are many applications for which reliable and safe robots are desired. For example, assistant robots for disabled or elderly people and surgical robots are required to be safe and reliable to prevent human injury and task failure. However, different levels of safety and reliability are required for different tasks so that understanding the reliability of robots is paramount. Currently, it is possible to guarantee the completion of a task when the robot is faulttolerant and the task remains in the fault-tolerant workspace. The traditional definition of faulttolerant workspace does not consider different reliabilities for the robotic manipulator’s different joints. The aim of this paper is to extend the concept of a fault-tolerant workspace to address the reliability of different joints. Such an extension can offer a wider fault-tolerant workspace while maintaining the required level of reliability. This is achieved by associating a probability with every part of the workspace to extend the fault-tolerant workspace. As a result, reliable fault-tolerant workspaces are introduced by using the novel concept of conditional reliability maps. Such a reliable fault-tolerant workspace can be used to improve the performance of assistant robots while providing the confidence that the robot remains reliable for completion of its assigned tasks.