D. Piccinini
Papers
1
Total Citations
9
H-Index
1
About
Dr. D. Piccinini is a roboticist whose research centers on autonomous perception and manipulation for humanoid robots operating in unstructured environments. A key contribution is their pioneering work on Next Best View (NBV) planning, where they developed a method that leverages the full-body movement primitives of humanoid platforms—such as bending, crouching, and stepping—to actively peer around occlusions. This approach, detailed in their most-cited paper (2019, 9 citations), allows a robot to systematically explore a region of interest in an initially unknown environment, using a depth sensor to build a complete model of a target object despite obstacles. By integrating motion planning with active perception, Piccinini’s work directly addresses the fundamental challenge of visual occlusion that plagues static sensor systems. This research has practical implications for disaster response and industrial inspection, where robots must navigate cluttered spaces. While still early in their career, Piccinini’s focus on exploiting a humanoid’s full kinematic capabilities for perception marks a significant step toward more autonomous and adaptable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1