Soft error assessment of attitude estimation algorithms running on resource-constrained devices under neutron radiation

There is a growing incorporation of unmanned aerial vehicles (UAVs) within remote and urban environments due to their versatility and ability to access hard-to-reach and/or congested places. UAVs offer low-cost solutions for many applications, including healthcare (e.g., medical supplies delivery) and surveillance during public events, protests, or emergencies (e.g., nuclear accident). However, drone utilisation in urban areas often relies on strict regulations to ensure safe and responsible operation. UAVs are subject to radiation-induced soft errors, and identifying the most vulnerable software and hardware components to radiation exposure is a advisable task, which is difficult to undertake. An essential task to UAVs correct operation is attitude estimation. This paper assesses the soft error reliability of three attitude estimation algorithms running on two resource-constrained microprocessors under neutron radiation. Results suggest that the extended Kalman filter (EKF) algorithm provides the best mean work to failure result for critical fault events, which is about 3× more than the indirect Kalman filter (IKF) and 1.5× more w.r.t. the novel quaternion Kalman filter algorithm (NQKF).</p

Assessment of radiation-induced soft error on unmanned surface vehicles

The presence of Unmanned Surface Vehicles (USVs) is increasingly frequent on lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and its reliable operation become primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of respectively existing and non-existent objects. Furthermore, results suggest that object detection algorithms running with the multi-core strategy ( FITSDC rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy.</p