The Wayfarer Modular Navigation Payload for Intelligent Robot

Infrastructure

Brian Yamauchiyamauchi@irobot.com

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 Bins Clear 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 Tracking Landscape 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