Arthur Torres Baiao

Universidade Federal de Itajubá

Papers

1

Total Citations

4

H-Index

1

About

Dr. Arthur Torres Baiao is a robotics researcher whose work focuses on multi-robot coordination and task allocation systems, with a particular emphasis on auction-based frameworks. His most-cited paper, "A Murdoch-Based ROS Package for Multi-robot Task Allocation" (2018, 4 citations), addresses the growing complexity of coordinating multiple robots in industrial applications by implementing an auction-based MRTA system using the Murdoch architecture. This contribution provides a practical, modular solution for deploying decentralized task allocation in real-world robotic systems, bridging the gap between theoretical algorithms and ROS-based implementations. While his citation count is still building, Dr. Baiao's work is significant for its focus on scalable, distributed decision-making—a critical challenge as robotics applications expand into logistics, manufacturing, and autonomous exploration. His research offers a foundation for students and engineers seeking to understand how market-based mechanisms can enable efficient collaboration among robot teams, making him a valuable voice in the evolving field of multi-agent systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
A Murdoch-Based ROS Package for Multi-robot Task Allocation
4 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Universidade Federal de Itajubá

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago