Perception of Pedestrian Avoidance Strategies of a SelfBalancing Mobile Robot Mobile robots moving in crowded environments have to navigate among pedestrians safely. Ideally, the way the robot avoids the pedestrians should not only be physically safe but also perceived safe and comfortable. Despite the rich literature in collisionfree crowd navigation, limited research has been conducted on how humans perceive robot behaviors in the navigation context. In this paper, we implement three local pedestrian avoidance strategies inspired by human avoidance behaviors on a selfbalancing mobile robot and evaluate their perception in a humanrobot crossing scenario through a largescale user study with 98 participants. The study reveals that the avoidance strategies positively affect the participantsxe2x80x99 perception of the robotxe2x80x99s safety, comfort, and awareness to different degrees. Furthermore, the participants perceive the robot as more intelligent, friendly and reliable in the last trial than in the first even with the same strategy.

Right of Way, Assertiveness and Social Recognition in HumanRobot Doorway Interaction We expand on previous work for negotiating humanrobot navigation contention around doorways to produce a more sociallycompliant autonomous robot behaviour. Our goal is to improve the integration of robots navigating in human environments by eliciting human recognition of the robotxe2x80x99s right of way. This is achieved by incorporating feedback from a user study of our previous system to create a more communicative, reciprocal, and assertive behaviour. Our contribution includes both the updated behaviour and a new user study that evaluates and compares the system to its predecessor. Results show that participants are more likely to respect the robotxe2x80x99s right of way given the new robot behaviour, but their responses also highlight the challenges of socially integrating robots into human spaces.