MRI: Development of an Autonomous Robotic Vehicle Instrument (ARVIN)

MRI：自主机器人车辆仪器 (ARVIN) 的开发

• 批准号: 0521675
• 负责人: Gabriel Elkaim
• 金额: $ 36万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-10-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0521675&HistoricalAwards=false
• 关键词: MRI; Development; Autonomous; Robotic; Vehicle

This project, developing a platform for research and training to serve as an instrument for evaluating robotic subsystem and supersystem performance, accelerates and enhances the evolution of autonomous vehicle subsystems and component parts by providing a baseline instrument to measure and assess the performance and capabilities of the various portions of a given autonomous vehicle design. This Autonomous Robotic Vehicle Instrument (ARVIN) is designed to allow simultaneous, parallel operation of multiple instruments, actuators, and software/hardware subsystems. Due to the common environment in which the items are operating, the ARVIN yields a precise, robust metric of comparative performance and capability of the item in question. Inherently rapidly reconfigurable by design of its network-centric architecture, the ARVIN enables quick, easy substitutions and augmentations of sensors and actuators on the evaluation platform; it is not a set of identical robot structures that join and reform to move or climb.The ARWIN tests, simulates, and validates subsystems and components in three tightly coupled hierarchical areas acknowledge as critical to advances in robotics vehicles:-Guidance, Navigation, and Control (GNC),-Sensor and Actuators Suites, and-Software and Network Architectures.The Autonomous Robotic Vehicle Instrument consists of an Argo Conquest 6x6 Off-road/Amphibious vehicle, heavily modified, and a Hardware-in-the-Loop (HIL) simulator for the vehicle. The vehicle will be fitted with ultrasonic sonar and SICK LiDAR for collision avoidance, fiber optic gyros, IMU's, and NavCom STARFIRE differential GPS receivers for guidance, a Pentium class PC-104 stack with high speed communication networks for control, and a Videre MEGA-STC-VAR stereoscopic high speed color camera for vision capture.In general, due to the incredibly high cost (in time and money) of constructing an autonomous vehicle of any kind, designs are rarely modified unless the mission cannot be completed by the original vehicle design. Very rarely are the initial trade-off studies revisited and explored to see what might have been done differently. Thus, the ARVIN should have profound impact on the kind of trade-off studies that most autonomous vehicle design programs have to-date been missing. Broader Impact: ARVIN allows students and researchers to gain experience on an actual, physical, autonomous rover. This kind of practical training in systems integration, sensor fusion, software architecture for real-time systems, and actual control systems implementations has much to offer. The Naval Postgraduate School and the Intelligent Robotics Group (IRG) at NASA-Ames has indicated interest and enthusiasm in collaborating and experimenting with the modular chassis that will result of the ARVIN. Contributing to further understand trade-offs for mobile robotics, the platforms will also be used for outreach. The ARVIN infrastructure should become a cost-effective general robotics toll that may be easily replicated at other institutions.

该项目开发了一个研究和培训平台，作为评估机器人子系统和超系统性能的工具，通过提供基线仪器来测量和评估给定自动驾驶车辆设计的各个部分的性能和能力，加速和增强了自动驾驶车辆子系统和组件的发展。这种自主机器人车辆仪器（ARVIN）的设计允许多个仪器、执行器和软件/硬件子系统同时并行操作。由于项目操作的共同环境，ARVIN产生了有关项目的比较性能和能力的精确，稳健的度量。通过其以网络为中心的架构设计，ARVIN具有固有的快速可重构性，可以在评估平台上快速，轻松地替换和增强传感器和执行器；它不是一组相同的机器人结构，它们相互连接并重新组合以移动或攀爬。ARWIN测试、模拟和验证了三个紧密耦合分层领域的子系统和组件，这些领域对机器人车辆的进步至关重要：制导、导航和控制（GNC），传感器和执行器套件，以及软件和网络架构。自主机器人车辆仪表包括一辆Argo Conquest 6x6越野/两栖车辆，经过大量改装，以及该车辆的硬件在环（HIL）模拟器。该车辆将配备用于避免碰撞的超声波声纳和SICK激光雷达，用于制导的光纤陀螺、IMU和NavCom STARFIRE差分GPS接收器，用于控制的奔腾级PC-104堆栈与高速通信网络，以及用于视觉捕获的Videre MEGA-STC-VAR立体高速彩色摄像机。一般来说，由于制造任何类型的自动驾驶汽车的成本（在时间和金钱上）高得令人难以置信，除非原始车辆设计无法完成任务，否则很少修改设计。很少有人重新审视和探索最初的权衡研究，看看有什么不同的做法。因此，ARVIN应该对迄今为止大多数自动驾驶汽车设计项目所缺失的权衡研究产生深远的影响。更广泛的影响：ARVIN允许学生和研究人员获得实际的、物理的、自主的漫游者的经验。这种在系统集成、传感器融合、实时系统的软件架构和实际控制系统实现方面的实践培训可以提供很多东西。美国海军研究生院和NASA-Ames的智能机器人小组（IRG）对合作和试验ARVIN的模块化底盘表示了兴趣和热情。为了进一步了解移动机器人的权衡，这些平台也将用于外展。ARVIN的基础设施应该成为一种具有成本效益的通用机器人，可以很容易地在其他机构复制。