Towards Resilient Autonomous Navigation of Drones
نویسندگان
چکیده
Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations these situations, usually perceptually degraded without good GNSS, it is critical have a reliable robust state estimation solution. The main body of literature robot focuses on developing complex algorithms favoring accuracy. Typically, approaches rely strong underlying assumption: the engine will not fail during operation. In contrast, we propose an architecture pursues robustness by considering redundancy heterogeneity both sensing algorithms. designed expect detect failures adapt behavior system safety. this end, present HeRO (Heterogeneous Redundant Odometry): stack running parallel supervised resiliency logic. This logic carries out three functions: a) perform confidence tests data quality algorithm health; b) re-initialize those might be malfunctioning; c) generate smooth estimate multiplexing inputs based their quality. estimates used guidance control modules mobility behaviors system. validation utility approach shown with real experiments flying for use case autonomous exploration subterranean environments, particular results from STIX event DARPA Subterranean Challenge.
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ژورنال
عنوان ژورنال: Springer proceedings in advanced robotics
سال: 2022
ISSN: ['2511-1256', '2511-1264']
DOI: https://doi.org/10.1007/978-3-030-95459-8_57