Daniel Torres

University of Colorado Boulder

Papers

1

Total Citations

16

H-Index

1

About

Daniel Torres is a leading researcher in field robotics, with a primary focus on autonomous exploration, multi-agent coordination, and human-robot teaming in extreme environments. His most influential work, "Flexible Supervised Autonomy for Exploration in Subterranean Environments" (2023, 16 citations), addresses a critical challenge in robotics: enabling autonomous systems to rapidly navigate and map unknown, GPS-denied subterranean spaces. This research, developed in the context of the DARPA Subterranean (SubT) Challenge, pioneered flexible supervisory frameworks that balance robot autonomy with human oversight, allowing teams of robots to efficiently explore complex underground networks. Torres's contributions have been instrumental in advancing real-world deployment of autonomous systems for search-and-rescue, mining, and defense applications. His work demonstrates how intelligent human-robot collaboration can overcome the limitations of fully autonomous systems in unpredictable environments. With a growing citation impact and recognition from the DARPA community, Torres continues to push the boundaries of field robotics, developing algorithms that enable robots to operate reliably where GPS and communication are unreliable.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Flexible Supervised Autonomy for Exploration in Subterranean Environments
16 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Colorado Boulder

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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