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As robots become increasingly complex, they must explain their behaviors togain trust and acceptance. However, it may be difficult through verbalexplanation alone to fully convey information about past behavior, especiallyregarding objects no longer present due to robots' or humans' actions. Humansoften try to physically mimic past movements to accompany verbal explanations.Inspired by this human-human interaction, we describe the technicalimplementation of a system for past behavior replay for robots in this toolpaper. Specifically, we used Behavior Trees to encode and separate robotbehaviors, and schemaless MongoDB to structurally store and query theunderlying sensor data and joint control messages for future replay. Ourapproach generalizes to different types of replays, including both manipulationand navigation replay, and visual (i.e., augmented reality (AR)) and auditoryreplay. Additionally, we briefly summarize a user study to further provideempirical evidence of its effectiveness and efficiency. Sample code andinstructions are available on GitHub athttps://github.com/umhan35/robot-behavior-replay.

Mixed-Reality Robot Behavior Replay: A System Implementation