Robotic Perception with Unconventional Sensors

机器人系统的自主性目前依赖于传统的传感器，如激光和摄像头。在有源电磁传感器的情况下，替代传感模式通常用于检测缺陷、裂缝和评估基础设施的完整性，然而，基础研究问题阻碍了它们用于机器人感知。该项目将开发理论和算法，以实现非传统传感器的定位、绘图和识别等感知任务。这项研究的结果有可能通过准确可靠的检查来提高关键民用基础设施维护技术的有效性，并减少对人为干预的需求。

Autonomy in robotic systems currently relies on conventional sensors such as lasers and cameras. Alternative sensing modalities as in the case of active electromagnetic sensors are commonly used to detect flaws, cracks and assess infrastructure’s integrity, however, fundamental research questions preclude their use for robotic perception. This project will develop the theory and algorithms to enable perception tasks such as localisation, mapping and recognition with unconventional sensors. The outcomes of this research have the potential to improve the effectiveness of critical civil infrastructure maintenance technology through accurate and reliable inspections, and the reduced need for human intervention.