ArticleFrontiers in robotics and AI2020
Development and Testing of Psychological Conflict Resolution Strategies for Assertive Robots to Resolve Human-Robot Goal Conflict.
Article in Frontiers in robotics and AI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Workers expect basic social skills but limited autonomy from future robots - a qualitative interview study and taxonomy for robot social skills.Frontiers in robotics and AI · 2026Article
- Never say never: exploring the effects of knowledge availability on agent persuasiveness in controlled physiotherapy motivation dialogues.Frontiers in artificial intelligence · 2026Article
- Bridging Requirements, Planning, and Evaluation: A Review of Social Robot Navigation.Sensors (Basel, Switzerland) · 2024Article
- Don't touch that dial: Psychological reactance, transparency, and user acceptance of smart thermostat setting changes.PloS one · 2023Article
- A Compliance-Reactance Framework for Evaluating Human-Robot Interaction.Frontiers in robotics and AI · 2022Article
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Authors and funding
3 authors.
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Abstract
As service robots become increasingly autonomous and follow their own task-related goals, human-robot conflicts seem inevitable, especially in shared spaces. Goal conflicts can arise from simple trajectory planning to complex task prioritization. For successful human-robot goal-conflict resolution, humans and robots need to negotiate their goals and priorities. For this, the robot might be equipped with effective conflict resolution strategies to be assertive and effective but similarly accepted by the user. In this paper, conflict resolution strategies for service robots (public cleaning robot, home assistant robot) are developed by transferring psychological concepts (e.g., negotiation, cooperation) to HRI. Altogether, fifteen strategies were grouped by the expected affective outcome (positive, neutral, negative). In two online experiments, the acceptability of and compliance with these conflict resolution strategies were tested with humanoid and mechanic robots in two application contexts (public:
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