Title: Conscience in Motion: Safe Decision-Making Towards Responsible Robotics
Abstract: As robots become increasingly integrated into our daily lives, ranging from household assistants to autonomous vehicles, ensuring that they make safe, reliable, and ethically sound decisions is more urgent than ever. In this talk, Yiwei will present her research on achieving provable safety for robots operating in uncertain, unstructured environments. She will begin by introducing a control-theoretic framework that provides a mathematical foundation for guaranteeing safety in probabilistic settings, while allowing the robot to accomplish its tasks without being overly conservative. Building on this, Yiwei will explore the challenge of collective safety in multi-agent systems, where robots must collaborate with heterogeneous teammates in a decentralized manner and make context-aware decisions. She will show how a novel responsibility reasoning approach, combined with rigorous control-theoretic methods, can lead to group intelligence with formal safety assurances. Next, Yiwei will discuss how to learn underdefined safety specifications by blending data-driven learning with control-theoretic techniques—addressing the question, “How safe is safe?” and enabling robots to adapt and refine safety constraints in real time. Yiwei will conclude by outlining a vision for responsible robotics — systems that not only guarantee physical safety, but also align their behavior with human values, comply with ethical and legal standards, and seamlessly integrate into sectors such as healthcare, transportation, and domestic environments.
Bio: Yiwei Lyu is a final-year Ph.D. candidate in the Department of Electrical and Computer Engineering at Carnegie Mellon University, advised by Dr. John Dolan. Her research in robotics sits at the intersection of control theory, machine learning, and social science, with broad interests in safe control and verification, behavior planning, and human-robot interaction. Specifically, she develops principled methods to enable safe robot autonomy in multi-agent systems, supporting effective collaboration among robots and between robots and humans in uncertain, dynamic environments. Yiwei is a recipient of the Qualcomm Innovation Fellowship and received an honorable mention for the Jane Street Graduate Research Fellowship. She was also recognized as an IEEE/ACM Human-Robot Interaction (HRI) Pioneer and named a 2024 MIT EECS Rising Star. Her work has earned best paper awards and nominations at multiple conferences, including AAMAS, AAAI, and IFAC CPHS, as well as workshops at ICRA, IROS, and IJCAI. Prior to joining CMU in 2019, Yiwei earned her Bachelor’s degree in Electronic and Information Engineering from the Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen).
