Tiago Fonseca
Papers
1
Total Citations
1
H-Index
1
About
Tiago Fonseca is a researcher at the forefront of intelligent assistive robotics, with a primary focus on multi-agent systems and autonomous navigation for mobility aids. His work centers on developing decentralized Multi-Agent Reinforcement Learning (MARL) frameworks to enable safe, side-by-side navigation of intelligent wheelchairs—a critical step toward seamless human-robot interaction in shared spaces. Fonseca’s major contribution lies in advancing beyond traditional single-agent approaches, pioneering the use of Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithms to coordinate multiple autonomous wheelchairs in dynamic environments. This shift addresses real-world challenges in crowded settings, such as hospitals or care facilities, where robots must negotiate movement without centralized control. His 2024 paper on this topic has already garnered early citations, signaling growing interest in his scalable, decentralized methodology. By merging robotics, reinforcement learning, and accessibility engineering, Fonseca is shaping the future of assistive technology—where intelligent wheelchairs not only navigate independently but also collaborate with one another, enhancing mobility and independence for users with disabilities.
Research Focus
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Top Papers
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