Aviel Atias

Papers

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About

Aviel Atias is a robotics researcher whose work focuses on the fundamental challenge of multi-robot motion planning (MRMP). His primary contribution lies in systematically analyzing the metrics that govern how sampling-based planners, particularly RRT-style algorithms, connect configurations in high-dimensional spaces. Atias demonstrated that the choice of distance metric is not merely a technical detail but a critical factor that directly regulates roadmap connectivity and, ultimately, planning efficiency. His most-cited work, "Effective Metrics for Multi-Robot Motion-Planning" (2018, 11 citations), provides a rigorous framework for evaluating and selecting metrics that improve the performance of multi-robot systems. By highlighting how seemingly subtle design choices can dramatically impact scalability and solution quality, Atias has given practitioners concrete guidance for building more reliable coordination algorithms. His research bridges the gap between theoretical motion planning and practical deployment, making it essential reading for anyone working on multi-agent systems, warehouse automation, or collaborative robotics.