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Title: Resilient Coordination and Learning in Networked Multi-Robot Teams

Speaker: Stephanie Gil, Assistant Professor in Computer Sciecne at Harvard University


Abstract:

Multi-robot systems are increasingly integrated into real-world applications, from autonomous vehicle fleets to search-and-rescue teams. Ensuring their coordination algorithms remain robust against unreliable communication, security threats, and corrupted data is essential. This talk explores how control and information exchange can enhance situational awareness and security in multi-robot networks. Consensus problems are at the core of many multi-agent coordination tasks, a key challenge is that classical results indicate failure when malicious agents exceed half of the network connectivity. This quickly leads to limitations in the practicality of many multi-robot coordination tasks. However, with the growing prevalence of cyber-physical systems comes novel opportunities for detecting attacks by using cross-validation with physical channels of information. We introduce the concept of stochastic observations of trust, where an agent’s trustworthiness is modeled probabilistically. Under this framework, consensus can be restored even when the number of malicious agents surpasses classical thresholds. We will present both theoretical insights and experimental results demonstrating how communication strategies can secure multi-robot distributed algorithms. Additionally, we will discuss new reinforcement learning approaches for sequential decision-making that incorporate real-time sensor data to handle partial observability and dynamic environments. Case studies include autonomous multi-robot routing for delivery and pickup tasks, as well as real-time rendezvous with sperm whales in Dominica.


Speaker Bio:

Stephanie is an Assistant Professor at the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University. Her research focuses on trust and coordination in multi-robot systems, with applications in security, communication, and autonomy. Her contributions to the field have been recognized through the DARPA Young Faculty Award (2024), the Office of Naval Research Young Investigator Award (2021), and the National Science Foundation CAREER Award (2019). She was also named a 2020 Sloan Research Fellow for her work at the intersection of robotics and communication. Prior to her appointment at Harvard, Stephanie was an Assistant Professor at Arizona State University (2018–2020) and held a Visiting Assistant Professorship at Stanford University in the summer of 2019. She earned her Ph.D. from CSAL at MIT, specializing in multi-robot coordination and control, and completed her B.S. at Cornell University.

 

 

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