Miguel Bustamante

Papers

Total Citations

H-Index

About

Miguel Bustamante is a robotics researcher whose work centers on autonomous navigation and perception for service robots. His key contributions lie in developing practical algorithms that enable mobile robots to move safely and interact intelligently with their environments. In his highly cited 2016 paper, Bustamante addressed the fundamental challenge of path planning by combining potential fields with the Levenberg-Marquardt algorithm (LMA), creating a robust method for trajectory optimization and obstacle avoidance that remains a reference in the field. He further advanced service robotics in his 2018 work on object detection, where he integrated RGBD sensor data with computational vision algorithms to significantly improve a robot’s ability to recognize and manipulate everyday objects. Though his citation counts are modest, his research is valued for its direct applicability to real-world robotic systems, bridging the gap between theoretical control and vision methods and practical implementation. Bustamante’s work continues to inform the development of more capable and autonomous service robots, making him a notable contributor to the advancement of mobile robotics and intelligent perception.