1st Edition
A half-day workshop examining what "safe enough" means when robots reason, communicate, and act with increasing autonomy, bringing together robotics, AI, cognitive science, and ethics.
Being present is not the same as being welcome.
Acronym: BESAFE
Format: Half-day workshop
Edition: First
Robots are no longer waiting in factories for instruction, they are stepping into our world, navigating our spaces, and learning to live among us. But even technically safe robots can feel unpredictable, opaque, or unsettling when their behavior is hard to understand.
As robots become part of everyday life, safety must be reimagined as something people experience through interaction, reasoning, and trust, rather than as engineering specifications. This shift is accelerated by advances in generative models, which enable robots to interpret context, generate responses, and adapt their behavior in dynamic scenarios.
As robots gain these capabilities, new forms of risk emerge-not only physical risks but also psychological and social ones. Systems that hallucinate, misinterpret intent, or act in ways that people cannot anticipate may compromise safety, even when no physical harm occurs.
Professor of Robot Ethics · UWE Bristol, UK
Leading researcher in cognitive robotics and the ethical governance of autonomous systems. Active in IEEE and British Standards initiatives for robot and AI ethics.
TBA - Alan Winfield will speak on the ethical implications of autonomous decision-making in robot systems and what meaningful safety standards might look like beyond physical harm.
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Important dates
We invite short position papers and contributions addressing challenges, emerging practices, or reflections on what constitutes appropriate and safe behavior in human-robot interaction-beyond physical collision avoidance.
Accepted contributions will be presented as short talks and posters, highlighting ongoing work, open challenges, and perspectives on safety in intelligent robotic systems.
Autonomy, alternatives, limitations, and risks of decision-making in generative AI-driven robots.
Safe and responsible integration of large language models into robotic systems and deployment frameworks.
Methodologies and benchmarks for evaluating socially safe robot behavior beyond collision avoidance.
Standards, certification pathways, and governance structures for AI-enabled and socially interactive robots.
Human trust, interpretability, explainability, and perceived safety in interactions with autonomous robots.
Balancing consistent, predictable behavior with adaptive responses in intelligent robot systems.
Ethical, societal, and policy implications of deploying generative AI-driven robots in everyday environments.
Combining insights from robotics, AI, cognitive science, design, and ethics for holistic safety approaches.
Understanding and designing for psychological safety, social comfort, and acceptable robot presence.
Topics are indicative, not exhaustive - interdisciplinary contributions beyond this list are warmly welcome.
Lund University, Sweden
PhD student in Robotics and Semantic Systems at Lund University. Focuses on smooth, natural, and effective collaboration between humans and robots through mixed-initiative interaction and intention recognition.
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University of Southern Denmark, DK
PhD student at SDU focusing on human-centered collaborative robotics, specifically human-to-robot trust, transparency, and adaptive robot behavior.
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Constructor University, Bremen, DE
PhD student whose research focuses on social navigation, human–robot interaction, and how adaptive robot behavior influences perceived safety and agency.
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University of Bonn, Germany
PhD student in the Humanoid Robots Lab at Bonn. Research focuses on safe and natural navigation behavior of robots in human-centric environments.
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TU Chemnitz
Assistant Professor for Pervasive Computing Systems. Research focuses on applied machine learning, human-robot interaction, and the development of intelligent autonomous systems for telerobotics and VR/AR.
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University of Twente, NL
Assistant Professor in Human Media Interaction. Research focuses on developing robots to enhance health and quality of life, including social-physical interaction, personalization, and long-term engagement.
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Research focuses on AI, Cognitive Science, and Human-Robot Interaction, with an emphasis on robotic systems that communicate appropriately with human users across industrial, service, and supervisory contexts.
Research focuses on navigation, manipulation, and active perception for legged and wheeled robots, as well as detecting humans, analyzing their motions, and generating personalized robot behavior.