Abigail Breitfeld
Papers
1
Total Citations
11
H-Index
1
About
Abigail Breitfeld advances the frontier of autonomous exploration, specializing in multi-objective ergodic search and dynamic information gathering for robotic systems. Her work addresses critical challenges in planetary exploration and search-and-rescue operations, where robots must navigate inaccessible environments using limited prior knowledge. Her most-cited paper, "Multi-Objective Ergodic Search for Dynamic Information Maps" (2023, 11 citations), introduces novel trajectory planning methods that balance competing objectives—such as maximizing information gain while minimizing energy consumption—in environments where maps evolve over time. This contribution enables robots to make real-time, adaptive decisions, significantly improving their efficiency in uncertain, dynamic terrains. Breitfeld’s research bridges theoretical optimization and practical deployment, offering scalable solutions for autonomous agents operating under constraints. Her work has been recognized for its potential to transform how robots explore hazardous or remote regions, from Martian landscapes to disaster zones. With a growing citation record and a focus on actionable algorithms, Breitfeld is establishing herself as a rising voice in robotics and autonomous systems, inspiring students and researchers to rethink how machines learn from and interact with complex, changing worlds.
Research Focus
Key Achievements
Top Papers
- 1Multi-Objective Ergodic Search for Dynamic Information Maps11 citations · 2023