Alon Shirizly

Technion – Israel Institute of Technology

Papers

Total Citations

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About

Alon Shirizly is a roboticist whose research focuses on advancing robotic dexterity, particularly through the study of in-hand manipulation and secure grasping strategies. His work bridges the gap between human-like manipulation capabilities and practical robotic systems, aiming to enable robots to handle complex, ever-changing environments with the same finesse as human hands. Shirizly’s most cited paper, "Survey of learning-based approaches for robotic in-hand manipulation" (2024, 18 citations), provides a comprehensive overview of how machine learning techniques are revolutionizing the ability of robots to manipulate objects within a single hand—a critical skill for tasks ranging from assembly to healthcare. He is also known for his pioneering work on gravity-based caging grasps, where a robot hand forms a basket-like shape to securely support objects against gravity using minimal finger contact. His 2020 paper on "Contact Space Computation of Two-Finger Gravity Based Caging Grasps Security Measure" (8 citations) formalized how to compute and evaluate the security of such grasps, while his 2022 follow-up (3 citations) extended these methods to planar objects, offering practical algorithms for grasp selection. Shirizly’s contributions are particularly notable for their focus on passive, energy-based stability, which reduces the need for complex sensing and control. His work has direct implications for warehouse automation, assistive robotics, and manufacturing, where simple, reliable grasping is essential.