| Autor: |
Nascimento LBP; Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.; Federal Institute of Rio Grande do Norte, Parnamirim 59143-455, Brazil., Barrios-Aranibar D; Electrical and Electronics Engineering Department, Universidad Católica San Pablo, Arequipa 04001, Peru., Santos VG; Federal Institute of Rio Grande do Norte, Parnamirim 59143-455, Brazil., Pereira DS; Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.; Federal Institute of Rio Grande do Norte, Parnamirim 59143-455, Brazil., Ribeiro WC; Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil., Alsina PJ; Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil. |
| Abstrakt: |
The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by covering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies. |
