Guilherme Lawless

University of Lisbon, Max Planck Institute for Intelligent Systems

Papers

Total Citations

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About

Guilherme Lawless is a robotics researcher whose work focuses on the frontiers of multi-robot coordination, cooperative perception, and autonomous tracking. His key contributions lie in developing scalable, real-time systems that enable teams of robots—from ground vehicles to micro aerial vehicles (MAVs)—to collaboratively localize themselves and track dynamic objects. His most impactful work, "An Online Scalable Approach to Unified Multirobot Cooperative Localization and Object Tracking" (2017, 33 citations), introduces a particle filter-based framework that reduces computational complexity from exponential to linear growth with team size, a critical advance for deploying large robot swarms. Lawless further extends this vision to aerial robotics in "Deep Neural Network-Based Cooperative Visual Tracking Through Multiple Micro Aerial Vehicles" (2018), where he tackles the challenging problem of small-scale object detection using DNNs on resource-constrained MAVs. His involvement in the SocRob@Home project (2019) demonstrates a commitment to translating these algorithms into real-world service robotics. By bridging theoretical scalability with practical deep learning, Lawless’s research paves the way for robust, cooperative autonomous systems in surveillance, search-and-rescue, and environmental monitoring.