Wilfredo Torres-Calderon
Papers
1
Total Citations
12
H-Index
1
About
Wilfredo Torres-Calderon is a pioneering researcher at the intersection of robotics, construction automation, and reinforcement learning. His work focuses on developing intelligent systems that enable unmanned ground vehicles to autonomously map and reconstruct complex indoor environments with high precision. His most-cited paper, "Reinforcement learning for high-quality reality mapping of indoor construction using unmanned ground vehicles" (2023, 12 citations), introduces a novel framework that leverages deep reinforcement learning to optimize navigation and data acquisition for reality capture in cluttered construction sites. This contribution addresses a critical bottleneck in digital twin creation, offering a scalable solution that reduces manual intervention while improving mapping fidelity. Torres-Calderon’s research has immediate implications for smart construction, facility management, and autonomous inspection, bridging the gap between robotics and civil engineering. His work is gaining traction among practitioners and academics alike, as evidenced by its citation impact within a short time since publication. By integrating adaptive learning algorithms with real-world deployment constraints, he is shaping the future of automated construction monitoring and digital infrastructure.
Research Focus
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Top Papers
- 1