Results 281 to 290 of about 20,695 (309)

Combinatorial maps for simultaneous localization and map building (SLAM)

2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), 2005
In this article, we focus on environment models for the well-known simultaneous localisation and map building (SLAM) problem, which has received considerable attention in the robotics community over the past few years. First, we compare different existing map representations to discuss their advantages and limitations in the scope of indoor robotics ...
Delphine Dufourd, Raja Chatila 0001, Dominique Luzeaux   +2 more
openaire   +1 more source

Sliding Mode SLAM for Robust Simultaneous Localization and Mapping

IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, 2018
Normal SLAMs use the extended Kalman filter to estimate robot localization and the mapping simultaneously. They do not work well under big disturbances and bounded noises. In this paper, the sliding mode method is applied for the SLAM. The proposed sliding model SLAM only requires the noises and the disturbances are bounded.
Salvador Ortiz 0001, Wen Yu 0001, Erik Zamora 0001   +2 more
openaire   +1 more source

A solution to the simultaneous localization and map building (SLAM) problem

IEEE Transactions on Robotics and Automation, 2001
The simultaneous localization and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location.
Gamini Dissanayake, Paul M. Newman, Steve Clark, Hugh F. Durrant-Whyte, M. Csorba   +4 more
openaire   +1 more source

Feature extracted algorithm for simultaneous localization and mapping (SLAM)

2015 IEEE International Conference on Consumer Electronics (ICCE), 2015
The problem of SLAM is still a challenging issue. When the number of landmarks increases, the accuracy of the estimated location of the robot decreases. Therefore, current measurement is filtered to avoid wrong landmarks. Then, triangulation is used to update the robot's pose. Simulation results show the success of the proposed algorithm.
Yan-Jhang Shih, Chen-Chien J. Hsu, Wei-Yen Wang, Yin-Tien Wang   +3 more
openaire   +1 more source

Topological Gaussian ARAM for Simultaneous Localization and Mapping (SLAM)

2012 International Symposium on Micro-NanoMechatronics and Human Science (MHS), 2012
This paper proposes a new neural architecture called Topological Gaussian ARAM (TGARAM) for Simultaneous Localization and Mapping (SLAM). TGARAM is integrating the Gaussian classifier with the incremental topology-learning mechanisms of the Growing Neural Gas (GNG) model for online learning of multidimensional inputs and topological map building.
Wei Hong Chin, Chu Kiong Loo
openaire   +1 more source

Filter design for simultaneous localization and map building (SLAM)

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2003
This paper deals with the fusion of random variables when cross covariances are unknown. This is a vital problem in nearly every real world application since cross covariances are often impossible to obtain, but also cannot be ignored. We provide a rigorous derivation of the fusion equations which are also known as covariance intersection.
Christian Schlegel, Thomas Kämpke
openaire   +1 more source

ROSLAM—A Faster Algorithm for Simultaneous Localization and Mapping (SLAM)

2016
Computationally efficient SLAM (CESLAM) has been proposed to solve simultaneous localization and mapping problem in real-time design. CESLAM first uses the landmark measurement with the maximum likelihood to update the particle states and then update their associated landmarks later.
Teng-Wei Huang, Chen-Chien J. Hsu, Wei-Yen Wang, Jacky Baltes   +3 more
openaire   +1 more source

An approach to appearance-based simultaneous localization and map building (SLAM)

IEEE Conference on Robotics, Automation and Mechatronics, 2004., 2005
Current robotic localization and SLAM algorithms are restricted to simple geometric features such as lines and corners as landmarks. The richness of the information provided by visual perception has not been fully explored. This paper presents a vision based SLAM algorithm which utilizes visual information with minimal prior assumptions.
Chun-Fan Lee, Arcot Sowmya
openaire   +1 more source

Adaptive Computation Algorithm for Simultaneous Localization and Mapping (SLAM)

2016
Computationally Efficient SLAM (CESLAM) was proposed to improve the accuracy and runtime efficiency of FastSLAM 1.0 and FastSLAM 2.0. This method adopts the landmark measurement with the maximum likelihood, where the particle state is updated before updating the landmark estimate. Also, CESLAM solves the problem of real-time performance. In this paper,
Da-Wei Kung, Chen-Chien J. Hsu, Wei-Yen Wang, Jacky Baltes   +3 more
openaire   +1 more source

SPM-SLAM: Simultaneous localization and mapping with squared planar markers

Pattern Recognition, 2019
Abstract SLAM is generally addressed using natural landmarks such as keypoints or texture, but it poses some limitations, such as the need for enough textured environments and high computational demands. In some cases, it is preferable sacrificing the flexibility of such methods for an increase in speed and robustness by using artificial landmarks ...
Rafael Muñoz-Salinas, Manuel J. Marín-Jiménez, Rafael Medina Carnicer   +2 more
openaire   +1 more source