Carlos H. C. Ribeiro
Instituto Tecnológico de Aeronáutica, Instituto de Aeronáutica e Espaço
Papers
22
Total Citations
303
H-Index
11
About
Carlos H. C. Ribeiro is a Brazilian researcher whose work spans the intersecting domains of autonomous robotics, reinforcement learning, multi-robot systems, and cognitive architectures for humanoid robots. His early and most influential contributions focused on accelerating machine learning through heuristic-guided reinforcement learning, with his 2007 paper on heuristic action selection accumulating 79 citations and establishing him as a notable voice in adaptive autonomous systems. This thread continued into RoboCup simulation research, where he applied these techniques to competitive multi-agent environments. Ribeiro's work has since broadened considerably, encompassing fault-tolerant and topologically robust multi-robot networks — a practical yet underexplored challenge in swarm robotics — with multiple papers addressing network resilience under robot failures. Simultaneously, he has pursued humanoid locomotion, developing model-free gait generation strategies and mixed-integer predictive controllers for dynamic walking. Perhaps most ambitiously, his CONAIM project ventures into machine consciousness, proposing attention-based cognitive architectures designed to give robots human-like awareness and selective perception. Supported in part by Brazil's FAPESP funding agency, Ribeiro's diverse yet coherent research agenda reflects a sustained commitment to building robots that are not only capable movers and communicators, but genuinely adaptive, resilient, and cognitively aware agents.
Research Focus
Key Achievements
Top Papers
- 1Accelerating autonomous learning by using heuristic selection of actions79 citations · 2007
- 2CONAIM: A Conscious Attention-Based Integrated Model for Human-Like Robots28 citations · 2016
- 3Heuristic Reinforcement Learning Applied to RoboCup Simulation Agents25 citations · 2008
- 4
- 5Mixed-integer programming for automatic walking step duration19 citations · 2016
- 6Toward fault‐tolerant multi‐robot networks19 citations · 2017
- 7Toward efficient adaptive ad-hoc multi-robot network topologies18 citations · 2018
- 8
- 9An Attentional Model for Autonomous Mobile Robots15 citations · 2016
- 10Stable and fast model-free walk with arms movement for humanoid robots14 citations · 2017