Zachary Tam

University of California, Berkeley, Berkeley Systems (United States)

Papers

Total Citations

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About

Zachary Tam is a robotics researcher focused on mechanical search, manipulation, and motion planning in cluttered, real-world environments. His work addresses the fundamental challenge of locating and extracting objects from constrained spaces, particularly shelves and bins, where visibility and access are limited. Tam’s most influential contributions include the development of the “Bluction” tool—a novel hybrid suction-blowing device that enables efficient stack and destack operations during mechanical search on shelves, and the AVPLUG framework for approach vector planning in unicontact grasping amid clutter. His papers have garnered over 26 citations, with his 2023 work on mechanical search with efficient stacking and destacking receiving 11 citations, and his 2022 “Bluction” paper earning 10 citations. Most recently, Tam introduced BOMP (Bin-Optimized Motion Planning), a framework that plans rapid pick-and-place motions for industrial robots using long-nosed suction tools, directly targeting productivity gains in logistics. Through these innovations, Tam is advancing the practical deployment of robots in warehouses, homes, and industrial settings, making automated retrieval from cluttered, occluded spaces more reliable and efficient.