Improving Visual Place Recognition Based Robot Navigation Through Verification of Localization Estimates

• URL: http://arxiv.org/abs/2407.08162v1
• Date: Thu, 11 Jul 2024 03:47:14 GMT
• Title: Improving Visual Place Recognition Based Robot Navigation Through Verification of Localization Estimates
• Authors: Owen Claxton, Connor Malone, Helen Carson, Jason Ford, Gabe Bolton, Iman Shames, Michael Milford,
• Abstract summary: This research introduces a novel Multi-Layer Perceptron (MLP) integrity monitor for Visual Place Recognition (VPR) It demonstrates improved performance and generalizability over the previous state-of-the-art SVM approach. We test our proposed system in extensive real-world experiments, where we also present two real-time integrity-based VPR verification methods.
• Score: 14.354164363224529
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Visual Place Recognition (VPR) systems often have imperfect performance, which affects robot navigation decisions. This research introduces a novel Multi-Layer Perceptron (MLP) integrity monitor for VPR which demonstrates improved performance and generalizability over the previous state-of-the-art SVM approach, removing per-environment training and reducing manual tuning requirements. We test our proposed system in extensive real-world experiments, where we also present two real-time integrity-based VPR verification methods: an instantaneous rejection method for a robot navigating to a goal zone (Experiment 1); and a historical method that takes a best, verified, match from its recent trajectory and uses an odometer to extrapolate forwards to a current position estimate (Experiment 2). Noteworthy results for Experiment 1 include a decrease in aggregate mean along-track goal error from ~9.8m to ~3.1m in missions the robot pursued to completion, and an increase in the aggregate rate of successful mission completion from ~41% to ~55%. Experiment 2 showed a decrease in aggregate mean along-track localization error from ~2.0m to ~0.5m, and an increase in the aggregate precision of localization attempts from ~97% to ~99%. Overall, our results demonstrate the practical usefulness of a VPR integrity monitor in real-world robotics to improve VPR localization and consequent navigation performance.

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