Papers
7
Total Citations
85
H-Index
4
About
Aviv Adler is a robotics researcher whose work lies at the intersection of motion planning, multi-robot systems, and autonomous manipulation. His most influential contribution is the development of efficient algorithms for multi-robot motion planning, particularly for unlabeled discs in simple polygons—a problem with broad applications in warehouse automation and swarm robotics. This foundational paper has garnered 54 citations, establishing him as a key voice in scalable coordination strategies. Adler has also advanced the practical frontier of robotic manipulation through his work on Push-MOG, a method that uses pushing actions to consolidate polygonal objects for multi-object grasping, significantly improving decluttering efficiency in home and industrial settings. His research further explores the role of heterogeneity in autonomous teams, investigating how varying defender speeds impact perimeter defense—a problem with implications for security and surveillance. With additional contributions to stochastic routing for kinodynamic vehicles and metrology, Adler demonstrates a rare ability to bridge theoretical rigor with real-world robotic challenges. His work continues to shape how robots plan, coordinate, and interact with complex environments.
Research Focus
Key Achievements
Top Papers
- 1Efficient Multi-Robot Motion Planning for Unlabeled Discs in Simple Polygons54 citations · 2015
- 2
- 3The Role of Heterogeneity in Autonomous Perimeter Defense Problems7 citations · 2022
- 4
- 5The role of heterogeneity in autonomous perimeter defense problems4 citations · 2024
- 6An efficient proximity probing algorithm for metrology3 citations · 2013
- 7