3D Trajectory Planning of Positioning Error Correction Based on PSO-A* Algorithm

Xing, Huaixi; Yu, Zhiwen; Zhang, Yuhui; Chen, You

doi:10.32604/cmc.2020.011858

Cited by 5 publications

(6 citation statements)

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“…T 1 represents a descriptive indicator of the total impact size per minute. In the energy section, the absolute value of torque is adopted to measure the energy consumption during the robot's motion process [22]. The relevant calculations are shown in Equation (12).…”

Section: B Csa Algorithm Process Design Integrating Multi-objective T...mentioning

confidence: 99%

Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm

Xia

2023

IEEE Access

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With the aging global population, there are more patients with hemiplegia caused by stroke. The demand for rehabilitation robots to assist rehabilitation therapists is also increasing. To solve the above problems, a reasonable trajectory planning of the rehabilitation robot joints is constructed to achieve rehabilitation assistance, improve safety and practicality.Firstly, a Kinematics model is constructed, and B-spline is applied to realize the trajectory planning of the rehabilitation robot. By introducing crow search algorithm and multiple crow search algorithms, the energy impact multi-objective optimization for the upper limb movement of the rehabilitation robot is carried out. Relevant experiments are designed to compare and verify the optimization effects of the algorithms. From the results, by optimizing the crow search algorithm, only 25.36% and 34.20% of the impact and energy are used. The average impact size per unit of time decreases by 74.68%. The energy consumption per unit time decreases by 65.39%.After optimizing the crow search algorithm, the impact and energy per unit time are only 14.41% and 17.25%, respectively. The energy per unit time decreases by 74.53%, and the impact decreases by 82.97%. Compared with other algorithms, the space complexity of the improved method is very small, and the standard deviation is 0.03. The optimization algorithm performs well in trajectory planning optimization. It is of great significance in the trajectory planning and rehabilitation role of rehabilitation robots.

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Section: B Csa Algorithm Process Design Integrating Multi-objective T...mentioning

confidence: 99%

Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm

Xia

2023

IEEE Access

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“…The common methods for achieving relative positioning in GNSS-denied environments can be classified into the following three categories: visual positioning [7][8][9][10][11][12][13][14][15][16][17], inertial navigation positioning [18][19][20][21][22], and radio positioning [23,24]. The development status of each category of positioning technology is systematically discussed below, and the advantages and limitations of each technology are analyzed, providing good inspiration for the study of relative positioning methods for MAVs in GNSS-denied environments.…”

Section: Introductionmentioning

confidence: 99%

“…The inertial navigation positioning is an autonomous method that provides accurate short-term navigation and positioning without relying on external information or emitting radiation. However, the general positioning system is prone to an error accumulation due to the second-order integration operation [18][19][20][21][22]. Various studies have been conducted to address this issue.…”

Section: Introductionmentioning

confidence: 99%

“…Various studies have been conducted to address this issue. For instance, a 3D trajectory planning method based on Particle Swarm Optimization-A star (PSO-A*) algorithm was proposed in [18] to solve the yaw problem of intelligent aircraft. In [19], the nonlinear error model was considered, and internal measurement information was utilized to correct the nonlinear error of inertial navigation.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Ranging and IMU-Based Method for Relative Positioning of Two-MAV Formation in GNSS-Denied Environments

Cheng

Ren

Deng

2023

Sensors

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Global Navigation Satellite Systems (GNSS) with weak anti-jamming capability are vulnerable to intentional or unintentional interference, resulting in difficulty providing continuous, reliable, and accurate positioning information in complex environments. Especially in GNSS-denied environments, relying solely on the onboard Inertial Measurement Unit (IMU) of the Micro Aerial Vehicles (MAVs) for positioning is not practical. In this paper, we propose a novel cooperative relative positioning method for MAVs in GNSS-denied scenarios. Specifically, the system model framework is first constructed, and then the Extended Kalman Filter (EKF) algorithm, which is introduced for its ability to handle nonlinear systems, is employed to fuse inter-vehicle ranging and onboard IMU information, achieving joint position estimation of the MAVs. The proposed method mainly addresses the problem of error accumulation in the IMU and exhibits high accuracy and robustness. Additionally, the method is capable of achieving relative positioning without requiring an accurate reference anchor. The system observability conditions are theoretically derived, which means the system positioning accuracy can be guaranteed when the system satisfies the observability conditions. The results further demonstrate the validity of the system observability conditions and investigate the impact of varying ranging errors on the positioning accuracy and stability. The proposed method achieves a positioning accuracy of approximately 0.55 m, which is about 3.89 times higher than that of an existing positioning method.

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“…The traditional 2D WSN has gradually been unable to meet the needs of the current society, such as smart city [19][20][21][22]. Some algorithms applied to 2D WSN must be extended to 3D WSN to adapt to new social needs.…”

Section: Introductionmentioning

confidence: 99%

Rotated Black Hole: A New Heuristic Optimization for Reducing Localization Error of WSN in 3D Terrain

Chai

Zheng

2021

Wireless Communications and Mobile Computing

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Wireless sensor network (WSN) attracts the attention of more and more researchers, and it is applied in more and more environment. The localization information is one of the most important information in WSN. This paper proposed a novel algorithm called the rotated black hole (RBH) algorithm, which introduces a rotated optimal path and greatly improves the global search ability of the original black hole (BH) algorithm. Then, the novel algorithm is applied in reducing the localization error of WSN in 3D terrain. CEC 2013 test suit is used to verify the performance of the novel algorithm, and the simulation results show that the novel algorithm has better search performance than other famous intelligence computing algorithms. The localization simulation experiment results reveal that the novel algorithm also has an excellent performance in solving practical problems. WSN localization 3D terrain intelligence computing rotated the black hole algorithm.

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3D Trajectory Planning of Positioning Error Correction Based on PSO-A* Algorithm

Cited by 5 publications

References 0 publications

Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm

Trajectory Planning Application of Rehabilitation Robots Based on Improved CSA Algorithm

A Novel Ranging and IMU-Based Method for Relative Positioning of Two-MAV Formation in GNSS-Denied Environments

Rotated Black Hole: A New Heuristic Optimization for Reducing Localization Error of WSN in 3D Terrain

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