Martin Miller

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About

Martin Miller is a leading researcher in robotics, with a primary focus on autonomous manipulation and haptic exploration. His work addresses the fundamental challenge of enabling robots to interact with unknown objects in unstructured environments. In his highly influential 2016 paper, "Local implicit surface estimation for haptic exploration," Miller pioneered methods for reconstructing object shape from noisy, incomplete sensory data—a critical step for autonomous grasping. This work, which has garnered 28 citations, provides a robust framework for robots to infer surface geometry through touch, bridging the gap between perception and action. Miller’s contributions are foundational for humanoid robotics, where the ability to grasp and manipulate novel objects is essential. By tackling the problem of shape estimation under uncertainty, he has advanced the field’s capacity for real-world, adaptive interaction. His research continues to inspire new approaches in haptic sensing and dexterous manipulation, making him a key figure in the development of more capable, autonomous robotic systems.