Mobile robot parallel PF-SLAM based on OpenMP

Jia, Songmin; Xiao, Yin; Li, Xiuzhi

doi:10.1109/robio.2012.6491017

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…In a SLAM navigation system, the process of data association is an important prerequisite for state estimation. Incorrect data association is likely to lead to serious deviation of estimation results [25,26]. At present, there are two data association algorithms commonly used in SLAM technology, that is, the nearest neighbor data association algorithm (NN, nearest neighbor) [27] and joint compatibility body & body data association algorithm (JCBB) [28].…”

Section: Data Association Algorithmmentioning

confidence: 99%

“…If there is a direct relative observation between the two nodes, the relative measurement information can be obtained directly by the sensor that carries on the relative observation. If the relative observation between the two nodes is with the help of the indirect relative observation of the surrounding landmark information, then the relative measurement information needs to be solved to a certain extent, and the concrete solution method can be combined (25) and then converted into the mobile robot.…”

Section: Single Node Measurement Updatementioning

confidence: 99%

See 1 more Smart Citation

Multirobot Collaborative Navigation Algorithms Based on Odometer/Vision Information Fusion

Guan

Liu

et al. 2020

Mathematical Problems in Engineering

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Collaborative navigation is the key technology for multimobile robot system. In order to improve the performance of collaborative navigation system, the collaborative navigation algorithms based on odometer/vision multisource information fusion are presented in this paper. Firstly, the multisource information fusion collaborative navigation system model is established, including mobile robot model, odometry measurement model, lidar relative measurement model, UWB relative measurement model, and the SLAM model based on lidar measurement. Secondly, the frameworks of centralized and decentralized collaborative navigation based on odometer/vision fusion are given, and the SLAM algorithms based on vision are presented. Then, the centralized and decentralized odometer/vision collaborative navigation algorithms are derived, including the time update, single node measurement update, relative measurement update between nodes, and covariance cross filtering algorithm. Finally, different simulation experiments are designed to verify the effectiveness of the algorithms. Two kinds of multirobot collaborative navigation experimental scenes, which are relative measurement aided odometer and odometer/SLAM fusion, are designed, respectively. The advantages and disadvantages of centralized versus decentralized collaborative navigation algorithms in different experimental scenes are analyzed.

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Section: Data Association Algorithmmentioning

confidence: 99%

Section: Single Node Measurement Updatementioning

confidence: 99%

Multirobot Collaborative Navigation Algorithms Based on Odometer/Vision Information Fusion

Guan

Liu

et al. 2020

Mathematical Problems in Engineering

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“…Clipp B et al [1] proposed that using stereo cameras as sensors achieve real-time visual SLAM. Jia S et al [2] proposed a parallel particle filter SLAM based on OpenMP. In this paper, a multi-thread particle filter technique is proposed to reduce the computation time and the execution time of SLAM.…”

Section: Introductionmentioning

confidence: 99%

An Effective FastSLAM Algorithm Based on CUDA

Zhang¹,

Liu²,

Zhu³

et al. 2016

IJGDC

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PPF: A parallel particle filtering library

Demirel¹,

Smal²,

Niessen³

et al. 2014

IET Conference on Data Fusion &Amp; Target Tracking 2014: Algorithms and Applications

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Abstract. We present the parallel particle filtering (PPF) software library, which enables hybrid shared-memory/distributedmemory parallelization of particle filtering (PF) algorithms combining the Message Passing Interface (MPI) with multithreading for multi-level parallelism. The library is implemented in Java and relies on OpenMPI's Java bindings for inter-process communication. It includes dynamic load balancing, multi-thread balancing, and several algorithmic improvements for PF, such as input-space domain decomposition. The PPF library hides the difficulties of efficient parallel programming of PF algorithms and provides application developers with a tool for parallel implementation of PF methods. We demonstrate the capabilities of the PPF library using two distributed PF algorithms in two scenarios with different numbers of particles. The PPF library runs a 38 million particle problem, corresponding to more than 1.86 GB of particle data, on 192 cores with 67% parallel efficiency.

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Mobile robot parallel PF-SLAM based on OpenMP

Cited by 9 publications

References 9 publications

Multirobot Collaborative Navigation Algorithms Based on Odometer/Vision Information Fusion

Multirobot Collaborative Navigation Algorithms Based on Odometer/Vision Information Fusion

An Effective FastSLAM Algorithm Based on CUDA

PPF: A parallel particle filtering library

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