Vincent Gherold
Papers
1
Total Citations
2
H-Index
1
About
Vincent Gherold is a roboticist whose research focuses on autonomous navigation, multimodal path planning, and energy-efficient locomotion. His most-cited work, "Self-Supervised Cost of Transport Estimation for Multimodal Path Planning" (2025, 2 citations), introduces a novel framework that enables robots to autonomously estimate the energetic cost of traversing diverse terrains. By leveraging self-supervised learning, Gherold’s approach allows robots to dynamically select optimal paths—whether rolling, walking, or crawling—without relying on pre-programmed models. This contribution is pivotal for field robotics, where energy efficiency directly impacts mission longevity and autonomy. Though early in his career, his work has already garnered attention for its practical implications in search-and-rescue and planetary exploration. Gherold’s research bridges the gap between theoretical planning algorithms and real-world deployment, offering a scalable solution for robots operating in unstructured environments. His achievements highlight a promising trajectory in advancing adaptive, energy-aware navigation systems.
Research Focus
Key Achievements
Top Papers
- 1