scholarly journals Autonomous navigation control based on improved adaptive filtering for agricultural robot

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142092535
Author(s):  
Weikuan Jia ◽  
Yuyu Tian ◽  
Huichuan Duan ◽  
Rong Luo ◽  
Jian Lian ◽  
...  
Keyword(s):  
Adaptive Filtering ◽  
Autonomous Navigation ◽  
Dynamic Performance ◽  
Variable Structure ◽  
Convergence Criteria ◽  
Agricultural Robots ◽  
Navigation Control ◽  
Navigation Accuracy ◽  
And Control ◽  
Agricultural Robot

Under the complex agricultural operation environment, reliable navigation system is the basic guarantee to realize the agricultural robot automated operation. This study focuses on improving navigation accuracy and control accuracy and conducts related research on autonomous navigation control of agricultural robots. This article discusses the advantages of using strict convergence criteria and combining Sage–Husa adaptive filtering with strong tracking Kalman filtering and then proposes an improved adaptive Kalman filter algorithm. The new algorithm can effectively suppress the filter divergence, improve the dynamic performance of the filter, and ensure its better filtering accuracy and strong adaptive ability to improve navigation accuracy of GPS. Further variable structure switching method is used to prevent proportional integral differential (PID) controller integral saturation phenomenon, which effectively solves the controller over-saturation problem. And combining this method with an improved adaptive filtering algorithm not only can effectively inhibit control interference but also achieve the anti-saturation effect, thereby enhancing the stability and accuracy of the control system. Finally, the simulation and experiment of the new method show that the proposed method greatly improves the ability of the filter to suppress divergence and control precision.

Research on Anti-Windup Controller of Autonomous Navigation Vehicle Based on Improved Adaptive Filter

2014 ◽  
Vol 1025-1026 ◽  
pp. 1119-1124
Author(s):  
Yun Zhang ◽  
Dean Zhao ◽  
Jun Zhang ◽  
Yun Liu
Keyword(s):  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Pid Control ◽  
Autonomous Navigation ◽  
Variable Structure ◽  
System Stability ◽  
Control Technique ◽  
Convergence Criterion ◽  
Control Precision ◽  
And Control

This paper presents relevant methods on navigation accuracy improvement of agricultural vehicle focusing on positioning accuracy and control precision. An adaptive kalman filtering, combination of Sage_Husa adaptive filtering and strong tracking kalman filtering based on strict convergence criterion, is adopted to improve filtering accuracy with strong ability of adaptive filtering and restraining filter divergence. A new variable-structure switching method to prevent PID controller from integrator windup can effectively solve the integral saturation phenomenon, which adopts a kind of adaptive adjustment rate to adjust the integral term of PID control algorithm. Finally, this paper puts the improved adaptive filtering and anti-windup variable-structure PID control technique into combination to effectively restrain interference and integral saturation, so as to achieve the purpose of improving system stability and control precision. The simulation and experiment results show that methods described above greatly enhance the capabilities of restraining filtering divergence and improving control precision.

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

Development of a Ring Permeability Test System

2010 ◽  
Vol 136 ◽  
pp. 153-157
Author(s):  
Yu Hong Du ◽  
Xiu Ming Jiang ◽  
Xiu Ren Li
Keyword(s):  
Control System ◽  
Control Method ◽  
Dynamic Performance ◽  
Experimental Tests ◽  
Measuring Method ◽  
Test System ◽  
Fluid Theory ◽  
And Control ◽  
Relationship Of ◽  
The Mathematical Model

To solve the problem of detecting the permeability of the textile machinery, a dedicated test system has been developed based on the pressure difference measuring method. The established system has a number of advantages including simple, fast and accurate. The mathematical model of influencing factors for permeability is derived based on fluid theory, and the relationship of these parameters is achieved. Further investigations are directed towards the inherent characteristics of the control system. Based on the established model and measuring features, an information fusion based clustering control system is proposed to implement the measurement. Using this mechanical structure, a PID control system and a cluster control system have been developed. Simulation and experimental tests are carried out to examine the performance of the established system. It is noted that the clustering method has a high dynamic performance and control accuracy. This cluster fusion control method has been successfully utilized in powder metallurgy collar permeability testing.

scholarly journals Practical Modeling of GNSS for Autonomous Vehicles in Urban Environments

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4236
Author(s):  
Woosik Lee ◽  
Hyojoo Cho ◽  
Seungho Hyeong ◽  
Woojin Chung
Keyword(s):  
Motion Estimation ◽  
Autonomous Vehicles ◽  
Autonomous Navigation ◽  
Urban Environments ◽  
Global Navigation Satellite Systems ◽  
Navigation Satellite ◽  
Key Technology ◽  
Satellite Systems ◽  
Agricultural Robots ◽  
Global Navigation Satellite

Autonomous navigation technology is used in various applications, such as agricultural robots and autonomous vehicles. The key technology for autonomous navigation is ego-motion estimation, which uses various sensors. Wheel encoders and global navigation satellite systems (GNSSs) are widely used in localization for autonomous vehicles, and there are a few quantitative strategies for handling the information obtained through their sensors. In many cases, the modeling of uncertainty and sensor fusion depends on the experience of the researchers. In this study, we address the problem of quantitatively modeling uncertainty in the accumulated GNSS and in wheel encoder data accumulated in anonymous urban environments, collected using vehicles. We also address the problem of utilizing that data in ego-motion estimation. There are seven factors that determine the magnitude of the uncertainty of a GNSS sensor. Because it is impossible to measure each of these factors, in this study, the uncertainty of the GNSS sensor is expressed through three variables, and the exact uncertainty is calculated. Using the proposed method, the uncertainty of the sensor is quantitatively modeled and robust localization is performed in a real environment. The approach is validated through experiments in urban environments.

scholarly journals RESEARCH ON REMOTE OPERATING SYSTEM OF PICKING ROBOT BASED ON BIG DATA AND WIFI

2021 ◽  
pp. 447-456
Author(s):  
Beibei Sun
Keyword(s):  
Operating System ◽  
Big Data ◽  
Remote Monitoring ◽  
Agricultural Production ◽  
Recognition System ◽  
Main Mode ◽  
Agricultural Robots ◽  
Remote Monitoring System ◽  
Modern Agriculture ◽  
And Control

Agricultural mechanization has become the main mode of agricultural production and represents the development direction of modern agriculture. The amount of data generated in the agricultural production process is extremely huge, so it is necessary to introduce the concept and analysis method of big data. Combining agricultural robots with big data can improve the performance and application effect of robots. This paper combines big data, WLAN technology and robot technology to realize man-machine remote cooperation platform. This gives full play to the advantages that people are good at object recognition and robots are good at execution, and improves the fruit picking efficiency. The target fruit positioning and recognition system aided by machine vision is adopted to realize the accurate positioning of the fruit to be picked. Design of LFM control signal fitting based on big data clustering. In order to verify the feasibility of the scheme, taking the tomato picking robot as an example, the communication error and control accuracy using big data and WIFI (Wireless Fidelity) technology were tested, and the positioning and navigation efficiency with and without remote monitoring system was compared. Test results show that using big data and WIFI remote monitoring technology can effectively improve the efficiency and accuracy of positioning and navigation of remote operating system, which is of great significance for the design of automatic control system of picking robot.

Sign in / Sign up

Export Citation Format

Share Document