Michael Boshra
Papers
3
Total Citations
16
H-Index
3
About
Michael Boshra’s research lies at the critical intersection of robotics, computer vision, and tactile sensing, with a focused emphasis on multimodal sensor integration for 3D object localization. His major contributions center on developing techniques that fuse visual data from monocular cameras with tactile data from planar-array sensors to robustly localize polyhedral objects, particularly in challenging scenarios such as an object held in a robot hand. Boshra’s work directly addresses a key limitation of single-sensor systems by demonstrating how combining complementary sensory modalities enhances both the efficiency and accuracy of object recognition and pose estimation. His most cited paper, "Localizing a polyhedral object in a robot hand by integrating visual and tactile data" (2000, 6 citations), along with closely related follow-up works (each garnering 5 citations), establishes a foundational framework for this hybrid approach. While his citation numbers reflect a specialized niche, his pioneering integration of vision and touch has informed subsequent research in dexterous manipulation and sensor fusion, making his contributions a notable early step toward more perceptive and adaptable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Use of visual and tactile data for generation of 3-D object hypotheses5 citations · 2002