SBIR-STTR Award

To conduct a target engagement, a team of autonomous unmanned air and ground vehicles will have to execute tasks of target pursuit and target tracking. The iRobot, CMU, and AeroVironment team is actively developing mission planning and collaborative teaming algorithms for a UAV-UGV team. For this project, we propose to expand the current team to double the number of participating UAVs and UGVs involved in a target engagement mission. Moreover, we aim to diversify the UGV set to include different but complementary UGV platforms that enable a wider range of capabilities for pursuit and tracking from the ground. The mission planning tools will be developed on a Supervisor Operator Control Unit to support mission monitoring, situational awareness and supervisory control for the operator. We lead the industry in our expertise of small UAV and UGV platforms as well as in advanced multi-robot coordination. The team has the collective knowledge and experience to develop practical near-term mission planning solutions and advanced collaborative UAV and UGV system teams.

Keywords:
Collaborative Engagement,Unmanned Systems,Fires And Effects,Autonomous Operations, Agents, Intelligent Systems, Robotics, Artificial Intelligence

The goal of MAGMA Phase II is to develop and demonstrate significant capabilities in UGV-UAV collaboration and sentry operations to support dangerous urban infantry missions, such as building clearing. To accomplish this goal effectively, the iRobot team will rely on established architectures and message sets developed under the Overseer and Collaborative Engagement projects, and continue system interoperability with ARDEC’s Multiple Platform Collaboration architecture. We will advance the collaborative capabilities developed under Collaborative Engagement to enable coordinated sentry and surveillance operations. The technical objectives of MAGMA Phase II incude applying collaborative engagement capabilities that PackBot and Raven systems to provide joint tasks in building surveillance, tracking and geo-locating of a dismounted target in an urban environment. Objectives also include designing and implementing algorithms for PackBots to detect persons entering or exiting a building, as well as designing and implementing an OCU display of geo-referenced UAV images via a map interface. We propose a PackBot-Raven team to conduct sentry operations, including building surveillance and stakeout at points of exit/entry. While the Raven sends back visual data to the operator, the PackBot will independently be processing its own visual data, using its onboard algorithms to help determine which data may be of interest, and it will send an alert message to the operator. Together, these two channels of information, made easily accessible on a single OCU, will allow operators to apply their military expertise to decide what subsequent human actions and robotic tasks may be necessary.

Keywords:
Packbot, Raven, Ugv-Uav Integration, Vehicle Autonomy, Geo-Location, Building Clearing, Door Detection, Target Tracking