Abstract-We investigate the effect of dominant and submissive movement strategies and a movement cue in a human-robot cooperation scenario on perceived predictability and trust. Four different movement strategies in proximal cooperation between a robot manipulator and a human participant were tested in an experiment in which participants had to arrange small objects in a shared workspace working on the same product as the robot. The features of the robot motion were characterized by dominance or a movement cue. The robot modifies its motion in two ways resulting in four different movement strategies: either it stops when the human is in danger of collision (submissive) or not (dominant), and either it performs a backing-off movement cue or not. The participants evaluated the movement strategies in terms of trust and predictability in a questionnaire. We found that the submissive backing-off movement strategy significantly enhanced the users' trust compared to the dominant movement strategy without movement cue. Other strategies showed no significant differences in trust or predictability.

Abstract-Ensuring the safety of humans in a collaborative environment with industrial robots is a major concern of human-robot co-working. Most current approaches give no formal guarantee of safety; where such guarantees are given, accounting for the unpredictability of the human may limit robot efficiency. We therefore developed a novel trajectory planner for a robot arm, which formally guarantees the safety of humans from collision with the robot for every possible human behaviour, without restricting the robot more than necessary. To achieve this, the trajectory planner verifies online that the robot adheres to two separate safety criteria derived from ISO standards using reachable occupancies of surrounding humans and the robot. While one criterion anticipates all possible movements of the human and provides a reasonable safety guarantee, the other criterion additionally guarantees strict safety as long as the human behaves as expected according to ISO standards. We implemented the trajectory planner for a real robot arm and show some experimental results.