Automated Environment Reduction for Debugging Robotic Systems



Complex environments can cause robots to fail. Identifying the key elements of the environment associated with such failures is critical for faster fault isolation and, ultimately, debugging those failures. In this work we present the first automated approach for reducing the environment in which a robot failed. Similar to software debugging techniques, our approach systematically performs a partition of the environment space causing a failure, executes the robot in each partition containing a reduced environment, and further partitions reduced environments that still lead to a failure. The technique is novel in the spatial-temporal partition strategies it employs, and in how it manages the potential different robot behaviors occurring under the same environments. Our study of a ground robot on three failure scenarios finds that environment reductions of over 95% are achievable within a 2-hour window.

Recommended citation: M. von Stein and S. Elbaum, 'Automated Environment Reduction for Debugging Robotic Systems,' 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 3985-3991, doi: 10.1109/ICRA48506.2021.9561997.

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