Share your thoughts, 1 month free Claude Pro on usSee more
WorkDL logo mark

db-CBS: Discontinuity-Bounded Conflict-Based Search for Multi-Robot Kinodynamic Motion Planning

About

This paper presents a multi-robot kinodynamic motion planner that enables a team of robots with different dynamics, actuation limits, and shapes to reach their goals in challenging environments. We solve this problem by combining Conflict-Based Search (CBS), a multi-agent path finding method, and discontinuity-bounded A*, a single-robot kinodynamic motion planner. Our method, db-CBS, operates in three levels. Initially, we compute trajectories for individual robots using a graph search that allows bounded discontinuities between precomputed motion primitives. The second level identifies inter-robot collisions and resolves them by imposing constraints on the first level. The third and final level uses the resulting solution with discontinuities as an initial guess for a joint space trajectory optimization. The procedure is repeated with a reduced discontinuity bound. Our approach is anytime, probabilistically complete, asymptotically optimal, and finds near-optimal solutions quickly. Experimental results with robot dynamics such as unicycle, double integrator, and car with trailer in different settings show that our method is capable of solving challenging tasks with a higher success rate and lower cost than the existing state-of-the-art.

Akmaral Moldagalieva, Joaquim Ortiz-Haro, Wolfgang H\"onig• 2023

Related benchmarks

TaskDatasetResultRank
Multi-Robot Motion PlanningUnicycle (UC) Swap (N=4, 5, 8, 10, 15, 20, 25, 30)
Success Rate100
16
Kinodynamic Multi-agent Path PlanningNarrow Corridor UC N=3
Success Rate (%)100
14
Multi-Robot Motion PlanningUnicycle (UC) Small Cluttered (N=3, 4, 5, 6, 7, 8, 10, 12, 15, 18, 20)
Success Rate100
8
Kinodynamic Multi-agent Path PlanningLarge Cluttered UC N=5
SR100
7
Multi-Robot Motion PlanningUnicycle (UC) Large Cluttered (N=4, 5, 8, 10, 15, 20, 25, 30)
Success Rate100
7
Kinodynamic Multi-agent Path PlanningSmall Cluttered SOC N=4
Success Rate (SR)0.00e+0
7
Kinodynamic Multi-agent Path PlanningSmall Cluttered SOC N=8
Success Rate (SR)0.00e+0
7
Kinodynamic Multi-agent Path PlanningSmall Cluttered SOC N=15
Success Rate0.00e+0
7
Kinodynamic Multi-agent Path PlanningLarge Cluttered UC N=20
Success Rate0.00e+0
7
Kinodynamic Multi-agent Path PlanningLarge Cluttered UC N=30
Success Rate (SR)0.00e+0
7
Showing 10 of 33 rows

Other info

Follow for update