Close proximity collaboration between humans and cobots remains particularly challenging.
However, new challenges arise when cobots are tasked with autonomous or semi-autonomous actions, resulting in additional stress for end-users. In Spatial Augmented Reality, with its known disadvantage of limited projection area size, established off-screen visualizations are not effective in communicating cobot perception and Line presents an easy-to-understand alternative. Overall, users prefer Line as a more straightforward visualization. Our findings show that Line, a lower complexity visualization, results in significantly faster reaction times compared to Halo, and lower task load compared to both Wedge and Halo. In a second remote experiment, we validated these findings with a broader non-specific user base. We compared the well-established visualizations Wedge and Halo against our proposed visualization Line in a remote user experiment with participants suffering from physical impairments. All of these communicate cobot perception by visually indicating which objects in the cobot’s surrounding have been identified by their sensors. To tackle this challenge, we compared three different visualization techniques for Spatial Augmented Reality. One significant aspect of predicting cobot behavior is understanding their perception and comprehending how they “see” the world. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, where they support people with physical impairments in their everyday lives. Nowadays, robots are found in a growing number of areas where they collaborate closely with humans.
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