Development of a low-cost full-stack Spatial AI system

机器人和无人机将改变我们生活的世界。虽然机器人组装、喷漆、焊接和材料处理等工业应用在历史上一直主导着市场，但今天，机器人和无人机数量的增长主要是由非工业应用推动的，如消费或企业机器人。机器人和无人机的新应用跨越了一系列不同的部门，包括自主农业、医学样本递送和个人助理。到2030年，英国天空预计将有7.6万架无人机，其中三分之一将改善公共服务；例如，支持紧急服务和搜救，勘测事件和犯罪现场，支持消防队调查燃烧的建筑(普华永道，2018年；Fly High，Nesta 2018)。所有机器人和自主系统都需要传感器来了解它们在现实世界中的位置，并在周围安全地移动。谷歌的自动驾驶汽车使用了激光雷达等基于激光的技术，结合保险杠安装的雷达、GPS和其他传感器；然而，尽管这些系统提供了最先进的性能，但对于许多机器人应用来说，它们过于昂贵、笨重和耗电。相机和其他成本较低的传感器，如加速计，可以安装在较小的机器人和无人机上，这些机器人和无人机在更广泛的市场上有应用，包括没有可靠GPS的环境；例如，在室内家居产品中。这些传感器使机器人或无人机能够查看周围环境并确定位置，这一过程被称为视觉同步定位和地图绘制(SLAM)。SLAMcore是一家总部位于伦敦的初创公司，由世界领先的计算机视觉和伦敦帝国理工学院的SLAM专家创立。我们的联合创始人安德鲁·戴维森教授在戴森的第一款机器人产品戴森360眼机器人吸尘器的核心设计了算法。我们正在开发的系统不仅可以定位和绘制机器人和无人机在其环境中的位置和地图，还可以使用人工智能来识别和响应它们周围的物体；例如，识别和跟踪人。在Innovate UK的资助下，SLAMcore将开发一个系统，该系统依赖于成本更低的传感器和计算机(树莓PI)，功耗更低，体积更小，支持创造新的市场，包括零售、酒店和医疗保健环境中的服务机器人。该项目将为英国和全球机器人和无人机行业提供新的技术能力(预计到2021年将达到2260亿美元；Tractica，2016)。

Robotics and drones are set to change the world we live in. While industrial applications such as robotic assembly, painting, welding, and materials handling have historically dominated the market, today, the growth in the number of robots and drones is driven largely by non-industrial applications, such as consumer or enterprise robots. The new applications of robotics and drones span a diverse range of sectors, including autonomous farming, medical sample deliveries, and personal assistants. Of the 76,000 drones predicted in the UK skies by 2030, one third will deliver improvements to public services; for example, supporting emergency services with search and rescue, surveying incident and crime scenes, and supporting the fire brigade in investigating burning buildings (PwC Drones Report, 2018; Flying High, Nesta 2018).All robotics and autonomous systems require sensors to understand where they are in the real world and safely move around in their surroundings. Laser-based techniques such as LiDAR are used in Google's self-driving cars, in combination with bumper-mounted radar, GPS, and other sensors; however, while these systems offer state-of-the-art performance, they are too expensive, bulky, and power hungry for many robotics applications. Cameras and other lower cost sensors such as accelerometers can be attached to smaller robots and drones that have application in a wider range of markets, including environments without reliable GPS; for example, in indoor household products. These sensors enable the robot or drone to view its surroundings and determine its location, in a process known as visual simultaneous localisation and mapping (SLAM).SLAMcore is a London-based start-up founded by world-leading computer vision and SLAM experts from Imperial College London. Our cofounder Professor Andrew Davison designed the algorithms at the heart of Dyson's first robotic product, the Dyson 360 Eye robot vacuum. We are developing systems that can not only position and map robots and drones in their environment, but use artificial intelligence to identify and respond to the objects around them; for example, recognising and tracking people.With funding from Innovate UK, SLAMcore will develop a system that relies on lower cost sensors and computer (Raspberry Pi), consumes less power, and has a smaller size, supporting the creation of new markets including service robots for retail, hospitality, and healthcare settings. The project will deliver a new technical capability for the UK and the global robotics and drones industry (predicted to reach USD 226billion by 2021; Tractica, 2016).