Daniel Plante
Papers
1
Total Citations
2
H-Index
1
About
Daniel Plante is a researcher in multi-robot systems and autonomous navigation, with a focus on practical, real-world deployment challenges. His most-cited work, "Area Coverage Optimization using Networked Mobile Robots with State Estimation" (2023, 2 citations), addresses a fundamental problem in robotics: how teams of mobile robots can efficiently cover a two-dimensional area when communication is limited or noisy. Plante’s key contribution lies in integrating state estimation into the coverage optimization process, allowing robots to operate effectively under the imperfect sensing and communication conditions typical of field environments. This work bridges the gap between theoretical coverage algorithms and the constraints of real-world deployment, such as signal degradation or intermittent connectivity. While his citation count is still growing, Plante’s research is notable for its emphasis on robustness and practicality, offering a foundation for future work in disaster response, environmental monitoring, and autonomous exploration. His approach is particularly valuable for students and researchers interested in networked robotics, distributed control, and the challenges of deploying autonomous systems in unstructured settings.
Research Focus
Key Achievements
Top Papers
- 1