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Small Robot Autonomy in an Integrated Environment

机译:集成环境中的小型机器人自治

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The U.S. Army Research Laboratory's (ARL) Computational and Information Sciences Directorate (CISD) has long been involved in autonomous asset control, specifically as it relates to small robots. Over the past year, CISD has demonstrated the ability to control and view streaming video from an FCS-surrogate PackBot robotic system over multiple network types (Soldier Radio Waveform (SRW), 802.11), as well as tasking the robot to follow both manually (ARL DigitalInk) and autonomously planned (CERDEC C2ORE) GPS waypoint routes. These capabilities remove the "stand alone system" limitations of traditional small robot systems and allow any and all data produced by such platforms to be available to anyone on the network, while at the same time reducing the amount of operator intervention required to utilize a robot. However, assumptions were made about the paths the robot was to traverse, specifically that they would be free from major obstacles.rnTo address these system limitations, CISD is implementing obstacle detection and avoidance (OD/OA) on the PackBot. The OD/OA utilizes COTS ranging sensors with indoor and/or outdoor capabilities, and leverages existing software algorithm components into the existing CISD robotic control architecture. These new capabilities are available in an integrated environment consisting of common command and control (C2) and network interfaces and on multiple platforms (ARL ATRV, LynchBot, PackBot, etc.) due to the modular and platformetwork independent architecture that ARL employs.rnThis paper will describe the current robotic control architecture employed by ARL and provide brief descriptions of existing capabilities. Further, the paper will discuss the small robot obstacle detection/avoidance integration effort performed by ARL, along with some preliminary results on its performance and benefits.
机译:美国陆军研究实验室(ARL)计算和信息科学局(CISD)长期以来一直参与自主资产控制,特别是涉及小型机器人。在过去的一年中,CISD展示了通过多种网络类型(士兵无线电波形(SRW),802.11)控制和查看来自FCS替代PackBot机器人系统的流视频的功能,并赋予了机器人手动跟踪这两种功能的能力( ARL DigitalInk)和自主计划的(CERDEC C2ORE)GPS航路点路线。这些功能消除了传统小型机器人系统的“独立系统”限制,并允许网络上的任何人都可以使用由此类平台产生的所有数据,同时减少了使用机器人所需的操作员干预量。但是,已经对机器人要经过的路径进行了假设,特别是它们不会遇到主要障碍。为了解决这些系统限制,CISD正在PackBot上实施障碍检测和避免(OD / OA)。 OD / OA利用具有室内和/或室外功能的COTS测距传感器,并将现有的软件算法组件利用到现有的CISD机器人控制架构中。由于ARL采用的模块化和平台/网络独立架构,这些新功能可在由通用命令和控制(C2)和网络接口组成的集成环境中以及在多个平台(ARL ATRV,LynchBot,PackBot等)上使用。 rn本文将描述ARL当前采用的机器人控制架构,并简要描述现有功能。此外,本文将讨论由ARL执行的小型机器人障碍物检测/避免集成工作,以及有关其性能和优点的一些初步结果。

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