Papers

3

Total Citations

41

H-Index

3

About

Marc Dalmasso is a researcher specializing in human-robot collaboration (HRC), with a particular focus on multi-agent path planning, collaborative navigation, and autonomous decision-making in shared environments. His work addresses one of robotics' most nuanced challenges: enabling robots and humans to communicate, negotiate, and execute joint plans effectively in real-world tasks. Dalmasso's most influential contribution, "Human-Robot Collaborative Multi-Agent Path Planning using Monte Carlo Tree Search and Social Reward Sources" (2021, 22 citations), introduced a sophisticated framework in which robots proactively compute coordinated plans for both themselves and human collaborators, integrating social reward signals to align robotic behavior with human expectations. This work built upon his earlier 2019 study exploring socially-aware reward structures in collaborative navigation search scenarios. His 2023 paper on shared task representation (14 citations) critically advances the field by addressing a recognized stagnation in human-robot collaborative navigation research, pushing beyond implicit collaboration toward explicit, structured task allocation frameworks. Collectively, Dalmasso's contributions have garnered over 40 citations, establishing him as a meaningful voice in bridging artificial intelligence planning techniques with socially intelligent robotics — work increasingly vital as collaborative robots enter complex, human-populated environments.

Research Focus

Key Achievements

3
H-Index
3
Papers
41
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Human-Robot Collaborative Multi-Agent Path Planning using Monte Carlo Tree Search and Social Reward Sources
22 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Institut de Robòtica i Informàtica Industrial

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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