Design of an Indoor Exploration and Multi-Objective Navigation System

In this paper, we propose an indoor robot autonomous navigation system. The robot firstly explores in an unknown environment, and then navigates autonomously by using the explored map. The robot is equipped a 2D laser scanner as the main sensor. The laser scanner is used for path planning and frontier-based exploration. A 2D global occupancy map is built for path planning, frontier-based exploration and multi-objective autonomous navigation. Laser scans are transmitted into Simultaneous Localization and Mapping (SLAM) process in the exploration phase. In indoor environment, the exploration efficiency is improved by merging a heuristic algorithm. By using multi-threading technology and a 3D perception approach proposed in this paper, the robot equipped with a low-cost RGBD sensor can detect all kinds of obstacles to achieve highly reliable navigation in complicated 3D environment. Meanwhile, we develop a multi-objective navigation application to make human-robot interaction more convenient and satisfy multi-task deployment. Our approaches are demonstrated by experimental results.

[1]  Brian Yamauchi,et al.  A frontier-based approach for autonomous exploration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[2]  S. Goodwin,et al.  C-Theta*: Cluster Based Path-Planning on Grids , 2015, 2015 International Conference on Computational Science and Computational Intelligence (CSCI).

[3]  Giuseppe Oriolo,et al.  Frontier-Based Probabilistic Strategies for Sensor-Based Exploration , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[4]  Henrik Karstoft,et al.  Map Building Based on a Xtion Pro Live RGBD and a Laser Sensors , 2014 .

[5]  Wolfram Burgard,et al.  Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[6]  Ashish Dutta,et al.  Path planning in dynamic environment for a rover using A∗ and potential field method , 2017, 2017 18th International Conference on Advanced Robotics (ICAR).

[7]  Sven Behnke,et al.  Evaluating the Efficiency of Frontier-based Exploration Strategies , 2010, ISR/ROBOTIK.

[8]  Omed Hassan Ahmed,et al.  Dijkstra algorithm applied: Design and implementation of a framework to find nearest hotels and booking systems in Iraqi , 2017, 2017 International Conference on Current Research in Computer Science and Information Technology (ICCIT).

[9]  Zheng Fang,et al.  A multi-objective strategy based on frontier-based approach and Fisher Information Matrix for autonomous exploration , 2013, 2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems.

[10]  Sven Behnke,et al.  Sancta simplicitas - on the efficiency and achievable results of SLAM using ICP-based incremental registration , 2010, 2010 IEEE International Conference on Robotics and Automation.

[11]  Shi Bai,et al.  Information-theoretic exploration with Bayesian optimization , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[12]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[13]  Alexei Makarenko,et al.  An experiment in integrated exploration , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.