An Atlas framework for scalable mapping

Bosse, Michael; Newman, Paul; Leonard, John J.; Soika, Martin; Feiten, Wendelin; Teller, Seth

doi:10.1109/robot.2003.1241872

Cited by 245 publications

(214 citation statements)

References 14 publications

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“…[16] The state matrix X predicts the position of the robot and the state vector of the landmark. Its dimension is 3 + 2N where N denotes the number of signs [18][19][20].…”

Section: Ekf-slammentioning

confidence: 99%

Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot

Wen

Miao

et al. 2017

J Intell Robot Syst

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The ability of autonomous navigation of the humanoid robot under unknown environment is very important to real-life applications. EKF-SLAM based on the camera recognition and laser detection for humanoid robot NAO is presented in this paper. Camera recognition is used to recognize if the object is a landmark. Because the computational resources needed for the feature-based position estimation are quite expensive, the laser instead of the camera provides the position of the landmark. A fractional

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“…[16] The state matrix X predicts the position of the robot and the state vector of the landmark. Its dimension is 3 + 2N where N denotes the number of signs [18][19][20].…”

Section: Ekf-slammentioning

confidence: 99%

Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot

Wen

Miao

et al. 2017

J Intell Robot Syst

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“…Bosse et al [12] proposed a hybrid approach by using a graph where each vertex represents a local frame (a local environment map) and each edge represents the transformation between adjacent frames. Loop closing is achieved via an efficient map matching algorithm.…”

Section: Previous Workmentioning

confidence: 99%

RAFI - A Stereo Vision Based Autonomous Mobile Area Mapping Robot with 16 DOF

Hossain¹,

Aziz²,

Rahman³

2013

IJAIA

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“…The grid is generated mainly from multilayer, high-resolution LIDAR data. Algorithms for the integration of low-resolution LIDAR data can be found in Biber and Strasser (2006), Bosse et al (2003), and Thrun (2002Thrun ( , 2003.…”

Section: Software Architecturementioning

confidence: 99%

Team AnnieWAY's autonomous system for the 2007 DARPA Urban Challenge

Kammel

Ziegler

Pitzer

et al. 2008

Journal of Field Robotics

208

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This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that successfully entered the finals of the 2007 DARPA Urban Challenge competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algorithms. Environmental perception mainly relies on a recent laser scanner that delivers both range and reflectivity measurements. Whereas range measurements are used to provide three-dimensional scene geometry, measuring reflectivity allows for robust lane marker detection. Mission and maneuver planning is conducted using a hierarchical state machine that generates behavior in accordance with California traffic laws. We conclude with a report of the results achieved during the competition. C 2008 Wiley Periodicals, Inc.

show abstract

An Atlas framework for scalable mapping

Cited by 245 publications

References 14 publications

Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot

Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot

RAFI - A Stereo Vision Based Autonomous Mobile Area Mapping Robot with 16 DOF

Team AnnieWAY's autonomous system for the 2007 DARPA Urban Challenge

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