Workshop on Introspective Methods for Reliable Autonomy

With respect to humans, introspection is the process of examining one’s internal state. Robots do not have thoughts neither feelings, only data, hardware and algorithms.

Therefore, robots can only assess the quality of sensor data, internal models, representations, information, perception input etc. Such knowledge can later lead to a modification of robots behavior by including the assessed quality score in the planning process.

Introspection relates to safety, active perception, mapping and many topics. These topics have a direct impact on a variety of research areas, such as long term autonomy, search and rescue, and many others. Long term autonomy can benefit from autonomous failure recovery and active learning. For Search and Rescue, estimation of the confidence of the sensor input and used maps is essential for overall risk assessment. Moreover, for a large variety of tasks assessing the quality of sensor data, internal models, representation, information will directly affect mission success. The ability to reason and solve its own failures, and proactively enrich owned knowledge is a direct way to improve autonomous behaviours of a robot.