Ramses Reyes
Papers
2
Total Citations
22
H-Index
2
About
Ramses Reyes is a robotics researcher whose work lies at the intersection of motion planning and vision-based control, with a focus on enabling autonomous systems to navigate dynamic, unstructured environments. His key contributions center on integrating Image-Based Visual Servoing (IBVS) with sampling-based planners, most notably through his development of Visual-RRT. In this approach, Reyes uses IBVS as a steering method within a Rapidly-exploring Random Tree (RRT) framework, allowing robots to generate collision-free paths while continuously adjusting to visual feedback—a critical capability for real-world tasks like road following and moving obstacle avoidance. His 2018 paper on integrating planning with IBVS for road following and obstacle avoidance, which has accumulated 13 citations, established a foundational strategy for representing robot plans as finite state machines. With a total of 22 citations across his most cited works, Reyes is recognized for bridging the gap between high-level task planning and low-level visual control, offering practical solutions for autonomous driving and mobile robotics. His work continues to influence researchers seeking robust, vision-guided navigation in cluttered, dynamic settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Visual-RRT: Integrating IBVS as a steering method in an RRT planner9 citations · 2023