James Jessup

Papers

Total Citations

H-Index

About

James Jessup is a robotics researcher whose work centers on autonomous mapping, multi-robot systems, and three-dimensional spatial representation. His most significant contributions lie in the development of robust techniques for merging 3D occupancy grid maps generated by teams of robots operating independently — a critical challenge in large-scale autonomous exploration where no single robot can feasibly survey an entire environment alone. Jessup's most impactful publication, "Robust and Efficient Multirobot 3-D Mapping Merging With Octree-Based Occupancy Grids" (2015), has accumulated 38 citations and addresses the fundamental problem of integrating independently constructed maps into a coherent global representation. His earlier work in 2014 laid the groundwork for this approach, introducing octree-based data structures as a memory-efficient means of representing complex 3D environments by recursively subdividing space — a technique that enables scalable mapping across large areas. Together, his three most-cited papers have garnered over 70 citations, reflecting meaningful influence within the robotics and autonomous systems community. For students entering the fields of simultaneous localization and mapping (SLAM), multi-robot coordination, or 3D environmental modeling, Jessup's research offers foundational methodologies for tackling real-world mapping challenges with computational efficiency and resilience to positional error.