Max Robotics — Global Service Robot Directory + US Certification

About

Carlos H. Llanos is a researcher whose work sits at the intersection of reconfigurable computing, robotics, and intelligent systems, with a particular focus on FPGA-based hardware acceleration for real-time applications. His contributions span mobile robotics, computer vision, and control systems, consistently demonstrating how custom hardware architectures can overcome the computational bottlenecks inherent in complex engineering tasks. Llanos has made significant strides in hardware implementations of algorithms rarely realized at the circuit level, including the Extended Kalman Filter for robot localization, background subtraction for moving object detection, and nonlinear model predictive control — each addressing demanding real-time constraints. His development of a parameterizable floating-point library for FPGAs provided foundational infrastructure for high-precision hardware computation. His opposition-based particle swarm optimization work, applied to mobile robot controllers, reflects a keen interest in bioinspired methods, further evidenced by his contributions to the UnB-Hand robotic hand, which integrates FPGA parallelism with bioinspired design optimization. With papers accumulating citations across robotics, image processing, sensor fusion, and kinematics — including multiple works exceeding 15 citations — Llanos has established himself as a productive bridge between theoretical algorithms and practical embedded hardware solutions, with real-world applications spanning surveillance, industrial robotics, and autonomous navigation.