Durrant-Whyte

Durrant-Whyte is a researcher known for developing the Monte Carlo Localization (MCL) algorithm in robotics. MCL helps robots determine their position and orientation within a map by using many random samples called particles. These particles represent possible locations, and as the robot gathers sensor data, the algorithm updates and refines these guesses, improving accuracy over time. This approach allows robots to navigate and operate effectively in uncertain or complex environments by probabilistically estimating their whereabouts, making movement and decision-making more reliable and robust.