Sep 2026· IAES International Journal of Robotics and Automation· Vol 15, pp. 589· 0 citations· 24 references
TL;DR
A ROS 2 frontier-allocation layer that combines a weighted frontier cost with global one-to-one matching is presented that isolates global matching from sequential assignment while keeping the cost formulation and ROS 2 execution stack fixed.
Abstract
Multi-robot frontier exploration supports warehouse mapping and inspection robotics, but geometric assignment can produce overlapping motion and inefficient target pairing. This paper presents a ROS 2 frontier-allocation layer that combines a weighted frontier cost with global one-to-one matching. The study isolates global matching from sequential assignment while keeping the cost formulation and ROS 2 execution stack fixed. Three policies are evaluated on two indoor maps, four team sizes, and three seeds. Across 72 completed main-policy runs, global matching gives the lowest mean completion time, travelled distance, path overlap, and assignment conflict. Relative to sequential cost-based assignment, it reduces completion time by 24.3%, travelled distance by 14.2%, and path overlap by 65.8%, with lower final coverage under the same stopping rule. The results support a coordination-efficiency benefit in the tested ROS 2 simulations; broader claims require larger, heterogeneous, dynamic, and physical deployments.
To address the trade-off between planning efficiency, path optimality, and trajectory tracking accuracy of mobile robot path planners under different spatial environments, this paper constructs square $(\mathbf{5 0 0} \times \mathbf{5 0 0})$ and elongated $(\mathbf{1 0 2 4} \times \mathbf{3 5 0})$ grid simulation maps...
Tian-Quan Feng· 2026 6th International Confe...· 0 citations
Multi-Agent Path Finding (MAPF) studies how to compute collision-free routes for multiple robots moving simultaneously on a shared map, a setting in which naive shortest-path behavior often leads to bottlenecks, deadlocks, and costly replanning. This paper proposes a hierarchical, reservation-based, multi-resolution pl...
Gicu Rata, Liviu Octavian Mafteiu-Scai· SAR Journal - Science and Re...· 0 citations
Large scale warehouse automation relies on efficient multi agent path finding (MAPF) to coordinate thousands of robots in structured environments. Existing MAPF algorithms primarily improve conflict resolution while representing warehouses as generic navigation graphs, overlooking their inherent geometric structure and...
This paper studies online multi-robot exploration and line coverage in unknown environments, where robots must explore the environment and service features without prior topology knowledge. The main challenge is that the feature graph is revealed incrementally, causing routing structure and workload allocation to updat...
Tian-Yuan Zheng, V. Veeraraghavan, Jin-Gang Yi et al.· 2026 IEEE 22nd International...· 0 citations
We present the dynamic rotation-stacked visibility graph (dRVG), an online motion planner that guides polygonal robots to specified goals in initially unknown, static environ- ments. It merges local roadmaps from successive observations to plan collision-free translations and rotations without a uniform position grid....
Duo Zhang, He-Chen Zhang, Jun-Shan Huang et al.· 0 citations
This paper presents an integrated framework for multi-robot task allocation and area coverage using an MQTT-based cloud communication architecture for waypoint delivery. A cost-based allocation strategy is proposed, incorporating factors such as battery level, robot age, approximate path distance, and number of turns...
Nithul Bagathi, S. Samarakoon, K. G. S. Apuroop et al.· Scientific Reports· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
