Next Article in Journal
A Capacitive Micromachined Ultrasonic Transducer-Based Resonant Sensor Array for Portable Volatile Organic Compound Detection with Wireless Systems
Next Article in Special Issue
Wi-PoS: A Low-Cost, Open Source Ultra-Wideband (UWB) Hardware Platform with Long Range Sub-GHz Backbone
Previous Article in Journal
A Combined Approach of Field Data and Earth Observation for Coastal Risk Assessment
Previous Article in Special Issue
Water Sink Model for Robot Motion Planning
Article

An Integrated Approach to Goal Selection in Mobile Robot Exploration

Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, 160 00 Prague, Czech Republic
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(6), 1400; https://doi.org/10.3390/s19061400
Received: 7 February 2019 / Revised: 8 March 2019 / Accepted: 13 March 2019 / Published: 21 March 2019
(This article belongs to the Collection Positioning and Navigation (Closed))
This paper deals with the problem of autonomous navigation of a mobile robot in an unknown 2D environment to fully explore the environment as efficiently as possible. We assume a terrestrial mobile robot equipped with a ranging sensor with a limited range and 360 ° field of view. The key part of the exploration process is formulated as the d-Watchman Route Problem which consists of two coupled tasks—candidate goals generation and finding an optimal path through a subset of goals—which are solved in each exploration step. The latter has been defined as a constrained variant of the Generalized Traveling Salesman Problem and solved using an evolutionary algorithm. An evolutionary algorithm that uses an indirect representation and the nearest neighbor based constructive procedure was proposed to solve this problem. Individuals evolved in this evolutionary algorithm do not directly code the solutions to the problem. Instead, they represent sequences of instructions to construct a feasible solution. The problems with efficiently generating feasible solutions typically arising when applying traditional evolutionary algorithms to constrained optimization problems are eliminated this way. The proposed exploration framework was evaluated in a simulated environment on three maps and the time needed to explore the whole environment was compared to state-of-the-art exploration methods. Experimental results show that our method outperforms the compared ones in environments with a low density of obstacles by up to 12.5 % , while it is slightly worse in office-like environments by 4.5 % at maximum. The framework has also been deployed on a real robot to demonstrate the applicability of the proposed solution with real hardware. View Full-Text
Keywords: path planning; routing; autonomous navigation; generalized traveling salesman problem; evolutionary algorithm path planning; routing; autonomous navigation; generalized traveling salesman problem; evolutionary algorithm
Show Figures

Figure 1

MDPI and ACS Style

Kulich, M.; Kubalík, J.; Přeučil, L. An Integrated Approach to Goal Selection in Mobile Robot Exploration. Sensors 2019, 19, 1400. https://doi.org/10.3390/s19061400

AMA Style

Kulich M, Kubalík J, Přeučil L. An Integrated Approach to Goal Selection in Mobile Robot Exploration. Sensors. 2019; 19(6):1400. https://doi.org/10.3390/s19061400

Chicago/Turabian Style

Kulich, Miroslav, Jiří Kubalík, and Libor Přeučil. 2019. "An Integrated Approach to Goal Selection in Mobile Robot Exploration" Sensors 19, no. 6: 1400. https://doi.org/10.3390/s19061400

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop