RObot SEArch in unkNown Environment
This repository contains algorihtms and data that we used for our work on robotic search that was presented in
Miroslav Kulich, Juan José Miranda-Bront, Libor Přeučil, A Meta-heuristic based Goal-Selection Strategy for Mobile Robot Search in an Unknown Environment, Computers & Operations Research, ISSN 0305-0548, http://dx.doi.org/10.1016/j.cor.2016.04.029.
The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a-priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e. a trajectory that is optimal in exploration does not necessarily minimize the expected value of the time to find an object along it. For this reason, we present a general framework that accounts for the particular characteristics of the search problem. Within this framework, an important decision involved in the determination of the trajectory can be formulated as an instance of the Graph Search Problem (GSP), a generalization of the well-known Traveling Deliveryman Problem (TDP) which has not received much attention in the literature. We developed a tailored Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for the GSP, which generates good quality solutions in very short computing times and is incorporated in the overall framework. The proposed approach produces very good results in a simulation environment, showing that it is feasible from a computational standpoint and the proposed strategy outperforms the standard approaches.
cmake is used to build the code, so just run the following in the main directory:
To see all provided options of the application run in the main directory:
These parameters can be set up at a command line or in the imr-exp.cfg file.
Run the application
buid/imr-exp -c imr-exp.cfg