Prepared for the Worst: A Learning-Based Adversarial Attack for Resilience Analysis of the ICP Algorithm

arXiv:2403.05666v1 Announce Type: cross
Abstract: This paper presents a novel method to assess the resilience of the Iterative Closest Point (ICP) algorithm via deep-learning-based attacks on lidar point clouds. For safety-critical applications such as autonomous navigation, ensuring the resilience of algorithms prior to deployments is of utmost importance. The ICP algorithm has become the standard for lidar-based localization. However, the pose estimate it produces can be greatly affected by corruption in the measurements. Corruption can arise from a variety of …

abstract adversarial algorithm algorithms analysis applications arxiv attacks autonomous cs.lg cs.ro deployments iterative lidar navigation novel paper prior resilience safety safety-critical type via