Towards resilient autonomous navigation of drones

Conference Article


International Symposium on Robotics Research (ISRR)





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Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a flying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.


aerospace robotics, mobile robots, robot programming.

Author keywords

Unmanned Aerial Vehicle, Drones

Scientific reference

A. Santamaria-Navarro, R. Thakker, D. D. Fan, B. Morrell and A. Agha-mohammadi. Towards resilient autonomous navigation of drones, 19th International Symposium on Robotics Research, 2019, Hanoi, Vietnam, pp. 922–937, 2022, Springer.