A5115028421- Inertial Sensor and Navigation
- Advanced Fiber Optic Sensors
- Target Tracking and Data Fusion in Sensor Networks
- Advanced Fiber Laser Technologies
- Autonomous Vehicle Technology and Safety
- Robotic Path Planning Algorithms
- Machine Fault Diagnosis Techniques
- Indoor and Outdoor Localization Technologies
- Time Series Analysis and Forecasting
- Reinforcement Learning in Robotics
- GNSS positioning and interference
Harbin Engineering University
2020-2022
Traditional calibration method is usually performed with expensive equipments suchas three-axis turntable in a laboratory environment. However practice, order to ensure theaccuracy and stability of the inertial navigation system (INS), it necessary recalibratethe measurement unit (IMU) without external equipment field. In this paper, anew in-field recalibration for triaxial accelerometer based on beetle swarm antenna search(BSAS) algorithm proposed. Firstly, as new intelligent optimization...
Fiber optic gyroscope (FOG) is one of the important components Inertial Navigation Systems (INS). In order to improve accuracy INS, it necessary suppress random error FOG signal. this paper, a variational mode decomposition (VMD) denoising method based on beetle swarm antenna search (BSAS) algorithm proposed reduce noise in Firstly, BSAS introduced detail. Then, permutation entropy band-limited intrinsic functions (BLIMFs) taken as optimization index, and two key parameters VMD algorithm,...
Gyroscope is a common inertial sensor for navigation system (INS). Its accuracy affected by various error sources and noises. Among them, the deterministic can be eliminated calibration. However, random difficult to evaluated due its uncertainty, so has great negative impact on of gyroscope. Therefore, in order improve precision gyroscope, it necessary compensate error. This paper proposes compensation method gyroscopes based support vector machine (SVM) beetle antennae search (BAS)...
In robotics, obstacle avoidance is an essential ability for distance sensor-based robots. This type of robot has axisymmetrically distributed sensors to acquire distance, so the state symmetrical. Training control policy with a reinforcement learning method trend. Considering complexity environments, such as narrow paths and right-angle turns, robots will have better if can steering direction speed simultaneously. paper proposes multi-dimensional action (MDAC) approach based on technique,...