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.
To 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 platform/network independent architecture that
This 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.