Bionic Path Planning Fusing Episodic Memory Based on RatSLAM

• Published in: Biomimetics (Basel, Switzerland) Vol. 8; no. 1; p. 59
• Main Authors: Yu, Shumei, Xu, Haidong, Wu, Chong, Jiang, Xin, Sun, Rongchuan, Sun, Lining
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.02.2023; MDPI
• Subjects: Algorithms; Artificial intelligence; bionic path planning; Cognitive ability; Cognitive models; Connectivity; connectivity networks; episodic cognitive map; Heuristic; Memory; Navigation systems; Neural networks; Neurons; RatSLAM; Robots; RatSLAM; connectivity networks; episodic cognitive map; bionic path planning
• ISSN: 2313-7673; 2313-7673
• DOI: 10.3390/biomimetics8010059

Inspired by rodents' ability to navigate freely in a given space, bionavigation systems provide alternatives to traditional probabilistic solutions. This paper proposed a bionic path planning method based on RatSLAM to provide a novel viewpoint for robots to make a more flexible and intelligent navigation scheme. A neural network fusing historic episodic memory was proposed to improve the connectivity of the episodic cognitive map. It is biomimetically important to generate an episodic cognitive map and establish a one-to-one correspondence between the events generated by episodic memory and the visual template of RatSLAM. The episodic cognitive map can be improved by imitating the rodents' behavior of memory fusion to produce better path planning results. The experimental results of different scenarios illustrate that the proposed method identified the connectivity between way points, optimized the result of path planning, and improved the flexibility of the system.