SCG '86 Proceedings of the second annual symposium on Computational geometry
New methods for computing visibility graphs
SCG '88 Proceedings of the fourth annual symposium on Computational geometry
Computational Geometry: Theory and Applications
Journal of Algorithms
Computers and Operations Research
Competition-based neural network for the multiple travelling salesmen problem with minmax objective
Computers and Operations Research - Special issue on the traveling salesman problem
A neural-network-based approach to the double traveling salesman problem
Neural Computation
Finding shortest safari routes in simple polygons
Information Processing Letters
Sensing Locations Positioning for Multi-robot Inspection Planning
DIS '06 Proceedings of the IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications
Information Sciences: an International Journal
Robust geometric computing and optimal visibility coverage
Robust geometric computing and optimal visibility coverage
Approximate solution of the multiple watchman routes problem with restricted visibility range
IEEE Transactions on Neural Networks
A Sensor Placement Algorithm for a Mobile Robot Inspection Planning
Journal of Intelligent and Robotic Systems
Delaunay refinement algorithms for triangular mesh generation
Computational Geometry: Theory and Applications
A study of a soft computing based method for 3D scenario reconstruction
Applied Soft Computing
| Hi-index | 0.00 |
Inspection planning is a problem of finding a (closed) shortest path from which a robot ''sees'' the whole workspace. The problem is closely related to the Traveling Salesman Problem (TSP) if the discrete sensing is performed only at the finite number of sensing locations. For the continuous sensing, the problem can be formulated as the Watchman Route Problem (WRP), which is known to be NP-hard for the polygonal representation of the robot workspace. Although several Self-Organizing Map (SOM) approaches have been proposed for the TSP, they are strictly focused to the Euclidean TSP, which is not the case of the inspection path planning in the polygonal domain. In this paper, a novel SOM adaptation schema is proposed to address both variants of the inspection planning with discrete and continuous sensing in the polygonal domain. The schema is compared with the state of the art SOM schema for the TSP in a set of multi-goal path planning problems and WRPs. The proposed algorithms are less computationally intensive (in order of tens) and provide better or competitive solutions.