H-TRIP: Exact Many-to-Many Distance Index for Multi-Robot Exploration
Overview
This paper introduces H-TRIP (Hierarchical Tropical Rank-one Incremental Propagation), a method for efficiently computing exact shortest-path distances in multi-robot exploration scenarios. The approach uses a spatial hierarchy and rank-one updates to handle growing occupancy grids, achieving significant speedups over traditional graph search methods while maintaining accuracy.
Generated from attributed reports · Updated 2 days ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Reported quantity · Robot count: 16 robots · Basis not reported
“experiments confirm exact agreement with reference searches on fully built maps and show that dense many-to-many queries at a few dozen viewpoints are up to two orders of magnitude faster than sequential k x BFS. On exploration runs with sixteen robots, in-loop queries on the growing occupancy graph are 2.21x-8.59x faster than co-scheduled k x BFS on maps with side 256, 512, and 1024 cells.”
Exact source · revision 1Source owner not reported
Reported quantity · speedup factor: 2.21 other · Basis not reported · Differing source assertions
“experiments confirm exact agreement with reference searches on fully built maps and show that dense many-to-many queries at a few dozen viewpoints are up to two orders of magnitude faster than sequential k x BFS. On exploration runs with sixteen robots, in-loop queries on the growing occupancy graph are 2.21x-8.59x faster than co-scheduled k x BFS on maps with side 256, 512, and 1024 cells.”
Exact source · revision 1Source owner not reported
Reported quantity · speedup factor: 8.59 other · Basis not reported · Differing source assertions
“experiments confirm exact agreement with reference searches on fully built maps and show that dense many-to-many queries at a few dozen viewpoints are up to two orders of magnitude faster than sequential k x BFS. On exploration runs with sixteen robots, in-loop queries on the growing occupancy graph are 2.21x-8.59x faster than co-scheduled k x BFS on maps with side 256, 512, and 1024 cells.”
Exact source · revision 1Source owner not reported
Reported quantity · map side length: 256 other · Basis not reported · Differing source assertions
“experiments confirm exact agreement with reference searches on fully built maps and show that dense many-to-many queries at a few dozen viewpoints are up to two orders of magnitude faster than sequential k x BFS. On exploration runs with sixteen robots, in-loop queries on the growing occupancy graph are 2.21x-8.59x faster than co-scheduled k x BFS on maps with side 256, 512, and 1024 cells.”
Exact source · revision 1Source owner not reported
Reported quantity · map side length: 512 other · Basis not reported · Differing source assertions
“experiments confirm exact agreement with reference searches on fully built maps and show that dense many-to-many queries at a few dozen viewpoints are up to two orders of magnitude faster than sequential k x BFS. On exploration runs with sixteen robots, in-loop queries on the growing occupancy graph are 2.21x-8.59x faster than co-scheduled k x BFS on maps with side 256, 512, and 1024 cells.”
Exact source · revision 1Source owner not reported
Reported quantity · map side length: 1024 other · Basis not reported · Differing source assertions
“experiments confirm exact agreement with reference searches on fully built maps and show that dense many-to-many queries at a few dozen viewpoints are up to two orders of magnitude faster than sequential k x BFS. On exploration runs with sixteen robots, in-loop queries on the growing occupancy graph are 2.21x-8.59x faster than co-scheduled k x BFS on maps with side 256, 512, and 1024 cells.”
Exact source · revision 1Source owner not reported
Report timeline
Follow attributed reports and material updates.
- arXiv Robotics — research abstractsSignalH-TRIP: Exact Many-to-Many Distance Index for Multi-Robot Exploration
This paper introduces H-TRIP (Hierarchical Tropical Rank-one Incremental Propagation), a method for efficiently computing exact shortest-path distances in multi-robot exploration scenarios. The approach uses a spatial hierarchy and rank-one updates to handle growing occupancy grids, achieving significant speedups over traditional graph search methods while maintaining accuracy.
Timezone · UTC
Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).