An Efficient Insect-inspired Approach for Visual Point-goal Navigation

• URL: http://arxiv.org/abs/2601.16806v1
• Date: Fri, 23 Jan 2026 14:57:04 GMT
• Title: An Efficient Insect-inspired Approach for Visual Point-goal Navigation
• Authors: Lu Yihe, Barbara Webb,
• Abstract summary: We develop a novel insect-inspired agent for visual point-goal navigation.<n>This combines abstracted models of two insect brain structures that have been implicated, respectively, in associative learning and path integration.<n>We demonstrate that the simple insect-inspired agent exhibits performance comparable to recent SOTA models at many orders of magnitude less computational cost.
• Score: 0.6445605125467574
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: In this work we develop a novel insect-inspired agent for visual point-goal navigation. This combines abstracted models of two insect brain structures that have been implicated, respectively, in associative learning and path integration. We draw an analogy between the formal benchmark of the Habitat point-goal navigation task and the ability of insects to learn and refine visually guided paths around obstacles between a discovered food location and their nest. We demonstrate that the simple insect-inspired agent exhibits performance comparable to recent SOTA models at many orders of magnitude less computational cost. Testing in a more realistic simulated environment shows the approach is robust to perturbations.

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