Brent Schlotfeldt
University of Pennsylvania, California University of Pennsylvania, Park University
Papers
10
Total Citations
251
H-Index
8
About
Brent Schlotfeldt is a robotics researcher specializing in multi-robot systems, active information gathering, and autonomous planning. His work sits at the intersection of probabilistic sensing, trajectory optimization, and decentralized coordination, with applications spanning environmental monitoring, search and rescue, surveillance, and active SLAM. Schlotfeldt's most influential contribution is his development of scalable planning algorithms for multi-robot active information acquisition. His 2018 paper on anytime decentralized planning (115 citations) introduced practical methods for designing sensing trajectories that reduce uncertainty about dynamic physical processes, while his 2019 work on asymptotically optimal, non-myopic planning (51 citations) pushed the field toward principled, long-horizon decision-making in complex environments. Together, these works established a foundation for efficient, theoretically grounded multi-robot coordination under uncertainty. Beyond core planning algorithms, Schlotfeldt has tackled critical real-world challenges including energy-aware coordination for heterogeneous robot teams, resilience in adversarial or failure-prone environments, and safe motion planning using multi-agent reinforcement learning. His research on non-monotone objective functions addresses a notoriously difficult optimization structure that arises when balancing information gain against energy costs. With over 250 total citations, Schlotfeldt's body of work has meaningfully advanced the theoretical and practical toolkit available to researchers building autonomous, collaborative robot systems.
Research Focus
Key Achievements
Top Papers
- 1Anytime Planning for Decentralized Multirobot Active Information Gathering115 citations · 2018
- 2
- 3Sampling-based planning for non-myopic multi-robot information gathering22 citations · 2021
- 4Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints13 citations · 2019
- 5
- 6
- 7Maximum Information Bounds for Planning Active Sensing Trajectories11 citations · 2019
- 8Steering for beacon pursuit under limited sensing8 citations · 2016
- 9Resilient Active Information Acquisition With Teams of Robots6 citations · 2021
- 10Resilient Active Information Gathering with Mobile Robots3 citations · 2018