Performance metrics and evaluation of a path planner based on genetic algorithms

Authors:
Giovanni Giardini;Tamás Kalmár-Nagy
Affiliations:
Politecnico di Milano, Milano, Italy;Texas A&M University, College Station, TX
Venue:
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Year:
2007

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Abstract

This paper focuses on the analysis of the performance of an innovative genetic path planner designed for a single agent exploration. The proposed method is a generalization of the well-known Traveling Salesman Problem (TSP) that we call Subtour problem and it can be formulated as finding the shortest possible path for visiting a subset of n given targets over a known area. The algorithm is based on a Genetic Algorithm coupled with a heuristic local search method. To evaluate the proposed planner, an extensive performance evaluation has been done.