R. Grinover
Papers
5
Total Citations
230
H-Index
5
About
R. Grinover is a roboticist whose work centers on autonomous manipulation, robotic vision, and cost-effective hardware design. Their most celebrated contribution is the development of Cartman, a low-cost Cartesian manipulator that won first place in the 2017 Amazon Robotics Challenge—a prestigious competition requiring teams to build pick-and-place robots for autonomous warehousing. The Cartman system, detailed in a highly cited 2018 paper (141 citations), demonstrated that affordable, custom-built hardware could outperform more expensive alternatives, challenging assumptions in the field. Grinover also made significant advances in robotic perception, particularly in semantic segmentation from limited training data (52 citations). Their approach enabled robots to recognize and grasp novel objects—including shiny and transparent items—in cluttered scenes, a key hurdle in the competition. By integrating multi-modal end-effector design with robust grasping algorithms, Grinover’s work has influenced both academic research and practical warehouse automation. Their achievements highlight how clever system-level design, rather than sheer computational power, can drive breakthroughs in real-world robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Semantic Segmentation from Limited Training Data52 citations · 2018
- 3
- 4
- 5Semantic Segmentation from Limited Training Data5 citations · 2017