Guillermo Cid Ampuero
Papers
1
Total Citations
4
H-Index
1
About
Guillermo Cid Ampuero is a robotics researcher whose work focuses on the intersection of deep reinforcement learning, sim-to-real transfer, and autonomous navigation for environmental applications. His primary research area involves developing low-cost, robust navigation systems for field robots, with a particular emphasis on beach-cleaning platforms. His most notable contribution is a 2025 study demonstrating how deep reinforcement learning policies can be successfully transferred from simulation to a real-world 30 kg differential-drive robot using only a minimal sensor suite—wheel-encoder odometry and a single 2-D LiDAR. This work addresses a critical challenge in outdoor robotics: achieving reliable autonomy on deformable, unstructured terrain like sand while keeping hardware costs low. By showing that a Raspberry Pi 4 can run these policies effectively, Cid Ampuero’s research opens the door to scalable, affordable robotic solutions for environmental cleanup. With 4 citations to his most-cited paper, his work is gaining early recognition for its practical impact, offering a compelling path toward deploying autonomous systems in real-world, resource-constrained settings.
Research Focus
Key Achievements
Top Papers
- 1