Papers
1
Total Citations
21
H-Index
1
About
Lu Ma is a roboticist whose research lies at the intersection of perception, manipulation, and autonomous learning. Her most-cited work, "Simultaneous Localization, Mapping, and Manipulation for Unsupervised Object Discovery" (2015, 21 citations), introduces a pioneering framework that integrates dense 3D SLAM with unsupervised object discovery using RGBD cameras and a robot manipulator. This system enables a robot to simultaneously build a map of its environment, track its own location, and discover, detect, and reconstruct unknown objects without any prior training—a significant step toward truly autonomous robots that can learn from unstructured environments. By combining appearance-based object detection with physical manipulation, Ma’s approach allows robots to actively interact with and understand their surroundings, moving beyond passive sensing. Her work is foundational for applications in domestic robotics, warehouse automation, and field exploration, where encountering novel objects is the norm. With 21 citations, this paper has influenced subsequent research in active perception and object-centric SLAM, establishing Ma as a key contributor to the growing field of robot autonomy and unsupervised learning in robotics.
Research Focus
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Top Papers
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