BBoE: Leveraging Bundle of Edges for Kinodynamic Bidirectional Motion Planning
Overview
This research presents BBoE, a bidirectional, kinodynamic motion planner that efficiently finds solutions in environments with varying obstacle density.
From arXiv Robotics — research abstracts
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 · number of systems: 4 other · Basis not reported
“a strategy to quickly find solutions in obstacle-rich spaces by leveraging a bundle of precomputed robot motions (i.e., edges); and ii) BBoE, a robust bidirectional kinodynamic planner that utilizes this strategy to produce fast and feasible solutions. Across four systems spanning 3D to 6D state spaces, BBoE is the only planner to achieve $\geq96\%$ success on every system while attaining the lowest planning time on”
Exact source · revision 1Source owner not reported
Reported quantity · number of systems with lowest planning time: 3 other · Basis not reported
“a strategy to quickly find solutions in obstacle-rich spaces by leveraging a bundle of precomputed robot motions (i.e., edges); and ii) BBoE, a robust bidirectional kinodynamic planner that utilizes this strategy to produce fast and feasible solutions. Across four systems spanning 3D to 6D state spaces, BBoE is the only planner to achieve $\geq96\%$ success on every system while attaining the lowest planning time on”
Exact source · revision 1Source owner not reported
Evidence dependency changes (1)
- 2026-10-31T17:27:42.809Z · evidence updated · source revision 1. Evidence extraction was updated; current source attributions are shown above.
Report timeline
Follow attributed reports and material updates.
- arXiv Robotics — research abstractsSignalBBoE: Leveraging Bundle of Edges for Kinodynamic Bidirectional Motion Planning
This research presents BBoE, a bidirectional, kinodynamic motion planner that efficiently finds solutions in environments with varying obstacle density.
Event coverage history
There is not enough continuous observation data to show a trend.
Timezone · UTC
Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).