Jack Spalding-Jamieson
Papers
1
Total Citations
5
H-Index
1
About
Jack Spalding-Jamieson is a researcher whose work sits at the intersection of computational geometry, robotics, and optimization. His most notable contribution comes from the CG:SHOP 2021 challenge, where his team, "gitastrophe," won by developing a novel approach to coordinated motion planning. Their winning method, detailed in "Coordinated Motion Planning Through Randomized k-Opt," tackled the problem of moving multiple square robots between configurations while minimizing total distance or makespan. By applying a randomized k-opt strategy, they produced highly efficient solutions to this complex combinatorial optimization problem. This work, which has garnered 5 citations, demonstrates his ability to combine algorithmic theory with practical, high-stakes competition. His research is particularly relevant for applications in warehouse automation, multi-agent systems, and any domain requiring efficient, collision-free coordination of moving entities. Spalding-Jamieson's achievement in the CG:SHOP challenge highlights his skill in developing creative, high-performance algorithms that push the boundaries of what is computationally feasible in motion planning.
Research Focus
Key Achievements
Top Papers
- 1Coordinated Motion Planning Through Randomized k-Opt (CG Challenge)5 citations · 2021