Papers
12
Total Citations
119
H-Index
5
About
Mauro Maya is a robotics researcher whose work spans parallel robot design, vision-based control, and mobile robot navigation — areas where he has made consistent and meaningful contributions over nearly two decades. His most recognized work examines the workspace and payload capacity of a reconfigurable Delta parallel robot (2013, 36 citations), introducing an innovative design that adjusts kinematic chain lengths symmetrically during operation, significantly expanding functional versatility. Building on this foundation, Maya has pioneered vision-based control strategies for Delta parallel robots, developing and refining Camera Space Manipulation techniques that enable precise tracking of moving objects without relying on complex kinematic models — work that has collectively garnered dozens of citations and remains practically relevant for high-speed industrial applications. Beyond parallel robots, Maya has addressed mobile robotics challenges, including sensor-based pose estimation for nonholonomic systems and robust indoor localization of robotic wheelchairs using particle filters. His 2021 work on a mobile manipulator with an adaptable passive suspension demonstrates a growing interest in autonomous systems for unstructured environments. With contributions spanning theoretical control design, mechanical innovation, and experimental implementation, Maya's research portfolio reflects a researcher committed to bridging rigorous mathematical foundations with real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1Workspace and Payload-Capacity of a New Reconfigurable Delta Parallel Robot36 citations · 2013
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- 10Sensor-based control of nonholonomic mobile robots3 citations · 2006