A Multi-Sensor Fusion Algorithm for Pedestrian Navigation Using Factor Graphs

An, Langping; Pan, Xianfei; Chen, Ze; Wang, Mang; Tu, Zheming; Chu, Coco

doi:10.23919/ccc52363.2021.9549777

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…Although a complete theoretical system and effective fusion algorithms have not been developed for multi-sensor data fusion, many mature and effective fusion methods have been proposed in many application areas according to their specific application contexts. [11][12][13][14] Kalman filtering is mainly used to fuse low-level real-time dynamic multi-sensor redundant data. The method uses recursion of the statistical properties of the measurement model to determine the optimal fusion and data estimation in a statistical sense.…”

Section: Multi-sensor Fusion Open Umbrella Condition Judgment Modelmentioning

confidence: 99%

Parachute control system of sounding rocket based on multi-sensor fusion

Wen

Li²,

Zhou³

et al. 2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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In this paper, a method for controlling the parachute opening device of a small sounding rocket through a multi-sensor fusion algorithm is proposed. This method uses IMU, airspeed tube and GNSS to obtain acceleration, velocity and position information respectively. After processing the three sets of data, the corresponding speed data is obtained, and the more accurate speed data is obtained through the Kalman filter algorithm. The vertical speed is used as the basis for the parachute-opening judgment condition and the timing of parachute-opening. Through simulation and experimental results, this method of parachute control of the sounding rocket proved to be very effective. This method can significantly reduce the accuracy requirements for the sounding rocket sensors, and obtain relatively high-precision results through the fusion processing of data collected by multiple low-precision sensors. This method can be used in the parachute control system of low-cost sounding rockets, which is of great significance for reducing the cost of small sounding rockets and promoting commercial applications.

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Section: Multi-sensor Fusion Open Umbrella Condition Judgment Modelmentioning

confidence: 99%

Parachute control system of sounding rocket based on multi-sensor fusion

Wen

Li²,

Zhou³

et al. 2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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A Robust Visual-Aided Inertial Navigation Algorithm for Pedestrians

Pan

et al. 2022

Journal of Sensors

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Real-time and robust state estimation for pedestrians is a challenging problem under the satellite denial environment. The zero-velocity-aided foot-mounted inertial navigation system, with the shortcomings of unobservable heading, error accumulation, and poorly adaptable parameters, is a conventional method to estimate the pose relative to a known origin. Visual and inertial fusion is a popular technology for state estimation over the past decades, but it cannot make full use of the movement characteristics of pedestrians. In this paper, we propose a novel visual-aided inertial navigation algorithm for pedestrians, which improves the robustness in the dynamic environment and for multi-motion pedestrians. The algorithm proposed combines the zero-velocity-aided INS with visual odometry to obtain more accurate pose estimation in various environments. And then, the parameters of INS have adjusted adaptively via taking errors between fusion estimation and INS outputs as observers in the factor graphs. We evaluate the performance of our system with real-world experiments. Results are compared with other algorithms to show that the absolute trajectory accuracy in the algorithm proposed has been greatly improved, especially in the dynamic scene and multi-motions trials.

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