The Wayfarer Modular Navigation Payload for Intelligent Robot Infrastructure Brian Yamauchi

Autonomous Urban Recon Critical Army need Daily casualties during patrols Hazards –Snipers –Improvised explosive devices –RPGs Teleop is not enough –Limited comms range –Line-of-sight restrictions –Limited bandwidth

Modular Navigation Infrastructure Wayfarer Modular Navigation Payload PackBot ► ◄ R-Gator FCS SUGV ▼

Wayfarer Objectives Focused, applied research project Develop technology to enable small UGVs to perform autonomous recon missions Enable small UGVs to: –Navigate autonomously down urban streets –Record digital video (EO/IR) and build map –Return autonomously to starting point –Provide video log and map to warfighters

Urban Reconnaissance Missions Perimeter Recon –Follow outside wall of building Route Recon –Follow current street for specified distance Street Recon –Follow GPS waypoints and street directions Record EO/IR video and build map Return to starting point

Wayfarer Sensors SICK LD OEM 360-degree planar LADAR Point Grey Bumblebee stereo vision system Organic GPS receiver Crossbow six-axis IMU Color and low-light B/W video cameras Indigo Omega FLIR camera Swiss Ranger 3D flash LADAR

Wayfarer PackBot

Scaled Vector Field Histogram (SVFH) Extension of Borenstein & Koren’s Vector Field Histogram (VFH) obstacle avoidance VFH: Map each range reading from sensors to corresponding polar coordinate sector SVFH: Spread each reading to vote for all sectors within an arc length inversely proportional to range:  = k / r  arc length (radians), k: constant (0.4), r: range (meters)

SVFH Hallway Example SVFH Bins Clear Vectors

SVFH Intersection Example SVFH BinsClear Vectors

Wayfarer Obstacle Avoidance

Perimeter Following Detect and follow building walls Hough Transform –Detects linear features in range data –Finds building walls and other street-aligned features (e.g. cars, curbs) –Collects votes to determine current wall heading Integrated with obstacle avoidance

Hallway Wall Detection Best LineAll Lines

Intersection Wall Detection Best LineAll Lines

Outdoor Perimeter Detection Wall TrackingLandscape Tracking

Wayfarer Perimeter Following

Autonomous Mapping Build occupancy grid map on robot Transmit local region back to OCU to minimize bandwidth usage Runs in parallel with navigation and avoidance Robot can travel beyond communications range and return with a map Can also run in background during teleoperation

Wayfarer Autonomous Mapping

Indoor Map

Localization Heading tracking using Hough transform –Track orientation of linear features –Use to estimate robot orientation Alternative approaches –Scan matching –GPS/Compass/INS –Kalman filters –Particle filters (Monte Carlo SLAM)

Future Work Outdoor testing of perimeter following Street following GPS-based street navigation

Conclusions Wayfarer will provide autonomous urban navigation technology for man-portable UGVs By September 2005, we will have two fully- operational Wayfarer UGV prototypes able to perform urban reconnaissance missions Wayfarer navigation payload will provide intelligent navigation infrastructure for PackBots and R-Gators, as well as FCS SUGV and other UGVs