RI: Small: Robust and Long-Term Visual Mapping and Localization

该项目使用低成本的视觉/深度相机和惯性传感器开发用于地图绘制和定位的健壮和持久的算法。开发了新的地图表示和算法，以提供计算高效的长期3D地图绘制和导航。研究主题包括增量式非高斯推理技术、密集映射、动态环境中的变化检测和语义理解。缺乏健壮性一直是以往定位技术的一个关键缺陷，阻碍了持续自主移动机器人系统的发展。扩展到多模式分布带来了巨大的智力困难。密集的方法正在改变机器人的感知，使其能够与物体进行复杂的物理交互，穿越楼梯，并在杂乱和受限的空间中进行安全的机动。尽管过去大多数机器人测绘研究都假设一个静态世界，但在这项拨款中开发的方法利用世界的动态来发现关于物体和地点的信息。这些进展正在室内、室外和水下环境中运行的机器人和便携式传感系统中进行测试。预期的影响跨越了广泛的应用，从机器人制造、医疗机器人、农业以及空间和水下探索，其中感知是关键要求。其他潜在的衍生产品包括房地产、建筑、设施维护、健康和安全领域的便携式地图应用。麻省理工学院在线机器人教育提供了一套机器人核心主题的在线课程材料，面向高中和大学教育的广泛受众。开源软件模块为用于教育和服务机器人应用的低成本机器人提供定位能力。

This project develops robust and persistent algorithms for mapping and localization using low-cost visual/depth cameras and inertial sensors. New map representations and algorithms are developed to provide computationally efficient long-term 3D mapping and navigation. Topics of investigation include incremental non-Gaussian inference techniques, dense mapping, change detection in dynamic environments, and semantic understanding. A lack of robustness has been a key shortcoming of previous techniques for localization, and thwarted the development of persistently autonomous mobile robot systems. Extension to multimodal distributions poses significant intellectual difficulties. Dense methods are transforming robotic perception, enabling sophisticated physical interaction with objects, traversal of stairs, and safe maneuvering in cluttered and confined spaces. Whereas most past research in robotic mapping has assumed a static world, the approach being developed in this grant exploits the dynamics of the world to discover information about objects and places. These advances are being tested for robotic and man-portable sensing systems operating in indoor, outdoor, and underwater environments. The expected impacts span a broad range of applications, from robotic manufacturing, medical robotics, agriculture, and space and underwater exploration, in which perception is a key requirement. Other potential spin-offs include human-portable mapping applications in real estate, construction, and facility maintenance, health and safety. MIT Online Robotics Education provides a set of online course materials for core topics in robotics, targeted to a broad audience for high school and college education. Open source software modules provide positioning capabilities for low-cost robots for education and service robotics applications.