Abstract
The application of mobile robots in autonomous navigation has contributed to the development of exploration tasks for the recognition of unknown environments. There are different methodologies for obstacles avoidance implemented in mobile robots; however, this research introduces a novel approach for a path planning of an unmanned ground vehicle (UGV) using the camera of a drone to get an aerial view that allows to recognize ground features through image processing algorithms for detecting obstacles and target them in a determined environment. After aerial recognition, a global planner with Rapidly-exploring Random Tree Star (RRT*) algorithm is executed, Dubins curves are the method used in this case for nonholonomic robots. The study also focuses on determining the compute time which is affected by a growing number of iterations in the RRT*, the value of step size between the tree’s nodes and finally the impact of a number of obstacles placed in the environment. This project is the initial part of a larger research about a Collaborative Aerial-Ground Robotic System.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yulong, D., Bin, X., Jie, C., Hao, F., Yangguang, Z., Guanqiang, G., Lihua, D.: Path planning of messenger UAV in air-ground coordination. IFAC-PapersOnLine 50, 8045–8051 (2017)
Sivaneri, V.O., Gross, Y.J.N.: UGV-to-UAV cooperative ranging for robust navigation in GNSS-challenged environments. Aerosp. Sci. Technol. 71, 245–255, 2017
Rahimi, R., Abdollahi, F., Naqshi, K.: Time-varying formation control of a collaborative heterogeneous multi agent system. Robot. Auton. Syst. 62, 1799–1805 (2014)
Melin, J., Lauri, M., Kolu, A., Koijonen, J., Ritala, R.: Cooperative sensing and path planning in a multi-vehicle environment. IFAC-PapersOnLine 198–203 (2015)
Rosa, L., Cognetti, M., Nicastro, A., Alvarez, P., Oriolo, G.: Multi-task cooperative control in a heterogeneous ground-air robot team. IFAC-PapersOnLine 48, 53–58 (2015)
Ropero, F., Muñoz, P., Moreno, M.D.R.: TERRA: a path planning algorithm for cooperative UGV-UAV exploration. Eng. Appl. Artif. Intell. (2019)
LaValle, S.: The RRT Page (1999). [En línea]. http://msl.cs.uiuc.edu/rrt/index.html
Abbadi, A., Prenosil, V.: Collided path replanning in dynamic environments using RRT and cell decomposition algorithms. Modelling and Simulation for Autonomous Systems: Second International Workshop, pp. 131–143 (2015)
Sieberth, T., Wackrow, R., Chandler, J.H.: Automatic detection of blurred images in UAV image sets. ISPRS J. Photogramm. Remote Sens. 122, 1–16 (2016)
Chernov, V., Alander, J., Bochko, V.: Integer-based accurate conversion between RGB and HSV color spaces. Comput. Electr. Eng. vol. 46, pp. 328–337, 2015
Huang, J., Feng, H., Xu, Z., Li, Q., Chen, Y.: A robust deblurring algorithm for noisy images with just noticeable blur. Optik 168, 577–589 (2018)
Chen, S., Li, D.: Image binarization focusing on objects. Neurocomputing 69, 2411–2415 (2006)
Dougherty, E.: Mathematical Morphology in image processing. Marcel Dekker, Nueva York (1993)
OpenCV.: OpenCV 2.4.13.7 documentation. [En línea]. https://docs.opencv.org/2.4/modules/imgproc/doc/filtering.html
Noreen, I., Khan, A., Habib, Z.: Comparison of RRT, RTT* and RRT*-smart path planning algorithms. IJCSNS Int. J. Comput. Sci. Netw. Secur. (2016)
Karaman, S., Frazzoli, E.: Sampling-based algorithms for optimal. Int. J. Robot. Res. (2011)
Yao, W., Qi, N., Zhao, J., Wan, N.: Bounded curvature path planning with expected length for Dubins vehicle entering target manifold. Robot. Auton. Syst. 97, 217–229 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Daniel Tenezaca, B., Canchignia, C., Aguilar, W., Mendoza, D. (2020). Implementation of Dubin Curves-Based RRT* Using an Aerial Image for the Determination of Obstacles and Path Planning to Avoid Them During Displacement of the Mobile Robot. In: Rocha, Á., Pereira, R. (eds) Developments and Advances in Defense and Security. Smart Innovation, Systems and Technologies, vol 152. Springer, Singapore. https://doi.org/10.1007/978-981-13-9155-2_17
Download citation
DOI: https://doi.org/10.1007/978-981-13-9155-2_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9154-5
Online ISBN: 978-981-13-9155-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)