Planning of Explanations for Robot Navigation
The choices made by autonomous robots in social settings bear consequences for humans and their presumptions of robot behavior. Explanations can serve to alleviate detrimental impacts on humans and amplify their comprehension of robot decisions. We model the process of explanation generation for robot navigation as an automated planning problem considering different possible explanation attributes. Our visual and textual explanations of a robot’s navigation are influenced by the robot’s personality. Moreover, they account for different contextual, environmental, and spatial characteristics. We present the results of a user study demonstrating that users are more satisfied with multimodal than unimodal explanations. Additionally, our findings reveal low user satisfaction with explanations of a robot with extreme personality traits. In conclusion, we deliberate on potential future research directions and the associated constraints. Our work advocates for fostering socially adept and safe autonomous robot navigation.