Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Robotic fish path planning in complex environment

Hou, N., Wang, H.ORCID: 0000-0003-2789-9530, Yu, M., Chen, L., Cao, Z., Zheng, J. and Man, Z. (2019) Robotic fish path planning in complex environment. In: Chinese Control Conference (CCC) 2019, 27 - 30 July 2019, Guangzhou, China

Link to Published Version:
*Subscription may be required


In this paper, ant colony (ACO) algorithm and steering model of robotic fish are combined for path planning. Firstly, an environmental model with multiple obstacles is established. Then, the ACO algorithm is used to generate feasible path. An optimal path is obtained which satisfies the principle of shortest path and least energy consumption. Sharp turns in the generated optimal path are replaced by small arcs that allow the robotic fish to move normally. Finally, a series of simulation experiments are carried out to verify the excellent performance and effectiveness of proposed algorithm.

Item Type: Conference Paper
Murdoch Affiliation(s): College of Science, Health, Engineering and Education
Item Control Page Item Control Page