Menandro Roxas

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About

Menandro Roxas is a robotics researcher whose work centers on 3D perception and robotic manipulation, with a particular focus on dense mapping and grasping. His most significant contribution is in variational fisheye stereo, where he developed a real-time method for generating dense 3D maps from wide-angle cameras without the need for explicit rectification or undistortion. This innovation, detailed in his 2020 paper (13 citations), is especially valuable for robotics applications like navigation and autonomous driving, where wide field-of-view sensors are critical. Roxas further refined this approach in a 2019 publication (3 citations), demonstrating its real-time feasibility. In the domain of robotic manipulation, his 2021 work on learning 6DoF grasping (2 citations) proposes a novel combination of imitation and reinforcement learning, using reward-consistent demonstration to simplify complex motion planning. By tackling both perception and action, Roxas contributes to more capable and autonomous robotic systems, bridging the gap between how robots see and how they interact with the world.