Flyphone: Visual Self-Localisation Using a Mobile Phone as Onboard Image Processor on a Quadrocopter
Journal of Intelligent and Robotic Systems
Efficient off-road localization using visually corrected odometry
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
6D scan registration using depth-interpolated local image features
Robotics and Autonomous Systems
Hopping odometry: motion estimation with selective vision
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
An efficient solution to 6DOF localization using unscented Kalman filter for planetary rovers
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Slip ratio for lugged wheel of planetary rover in deformable soil: definition and estimation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
On the error analysis of vertical line pair-based monocular visual odometry in urban area
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Wide-angle Visual Feature Matching for Outdoor Localization
International Journal of Robotics Research
Monocular omnidirectional visual odometry for outdoor ground vehicles
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Wide-baseline stereo vision for terrain mapping
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
Field Testing of an Integrated Surface/Subsurface Modeling Technique for Planetary Exploration
International Journal of Robotics Research
A new software architecture for developing and testing algorithms for space exploration missions
Intelligent Service Robotics
Robotics and Autonomous Systems
International Journal of Computer Vision
Stereo-vision-based navigation of a six-legged walking robot in unknown rough terrain
International Journal of Robotics Research
International Journal of Robotics Research
Cyber-Physical Challenges for Space Systems
ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
Field trial results of planetary rover visual motion estimation in Mars analogue terrain
Journal of Field Robotics
Field testing of visual odometry aided by a sun sensor and inclinometer
Journal of Field Robotics
Real time egomotion of a nonholonomic vehicle using LIDAR measurements
Journal of Field Robotics
Challenging data sets for point cloud registration algorithms
International Journal of Robotics Research
Monocular visual odometry and obstacle detection system based on ground constraints
ICSR'12 Proceedings of the 4th international conference on Social Robotics
Geometric particle swarm optimization for robust visual ego-motion estimation via particle filtering
Image and Vision Computing
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NASA's two Mars Exploration Rovers (MER) have successfully demonstrated a robotic Visual Odometry capability on another world for the first time. This provides each rover with accurate knowledge of its position, allowing it to autonomously detect and compensate for any unforeseen slip encountered during a drive. It has enabled the rovers to drive safely and more effectively in highly sloped and sandy terrains and has resulted in increased mission science return by reducing the number of days required to drive into interesting areas. The MER Visual Odometry system comprises onboard software for comparing stereo pairs taken by the pointable mast-mounted 45 deg FOV Navigation cameras (NAVCAMs). The system computes an update to the 6 degree of freedom rover pose (x, y, z, roll, pitch, yaw) by tracking the motion of autonomously selected terrain features between two pairs of 256×256 stereo images. It has demonstrated good performance with high rates of successful convergence (97% on Spirit, 95% on Opportunity), successfully detected slip ratios as high as 125%, and measured changes as small as 2 mm, even while driving on slopes as high as 31 deg. Visual Odometry was used over 14% of the first 10.7 km driven by both rovers. During the first 2 years of operations, Visual Odometry evolved from an “extra credit” capability into a critical vehicle safety system. In this paper we describe our Visual Odometry algorithm, discuss several driving strategies that rely on it (including Slip Checks, Keep-out Zones, and Wheel Dragging), and summarize its results from the first 2 years of operations on Mars. © 2006 Wiley Periodicals, Inc.