Survey, comparison and research challenges of IoT application protocols for smart farming

In industrial environments, over several decades, Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) have served to improve efficiencies of intralogistics and material handling tasks. However, for system integrators, the choice and effective deployment of improved, suitable and reliable communication and control technologies for these unmanned vehicles remains a very challenging task. Specifics of communication for AGVs and AMRs imposes stringent performance requirements on latency and reliability of communication links which many existing wireless technologies struggle to satisfy. In this paper, a review of latest AGVs and AMRs research results in the past decade is presented. The review encompasses results from different past and present research domains of AGVs. In addition, performance requirements of communication networks in terms of their latencies and reliabilities when they are deployed for AGVs and AMRs coordination, control and fleet management in smart manufacturing environments are discussed. Integration challenges and limitations of present state-of-the-art AGV and AMR technologies when those technologies are used for facilitating AGV-based smart manufacturing and factory of the future applications are also thoroughly discussed. The paper also present a thorough discussion of areas in need of further research regarding the application of 5G networks for AGVs and AMRs fleet management in smart manufacturing environments. In addition, novel integration ideas by which tactile Internet, 5G network slicing and virtual reality applications can be used to facilitate AGV and AMR based factory of the future (FoF) and smart manufacturing applications were motivated.

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A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

Nowadays, global engineers need to be equipped with professional skills and knowledge to solve 21st century problems. The educational program, created in digital learning rooms of the Higher Engineering Education Alliance Program (HEEAP) program supported by Arizona State University, became a pioneer in teaching learners to work within the community. First, the combination of a novel instructional strategy and an integrated education in which project-based approach is employed to apply the technical knowledge. During this, students in mechatronics, computer science, and mechanics must collaborate with peers from industrial systems engineering. Second, in this paper, the design of an open structure connecting multi-disciplinary major is illustrated with a new teaching approach. It is proved to be better by combining specialized understandings of various types in a wide range of applications. From this basis support, participants could implement additional components quickly while keeping the cost low, making the products feasible and user-friendly. Last but not least, students are facilitated with a free library that helps to control simply despite lacking experience in robotics or automation. Several examples show that students are capable of developing things by themselves on open design. In brief, this platform might be an excellent tool to teach and visualize the practical scenario in a multi-disciplinary field.

Design of an Open Platform for Multi-Disciplinary Approach in Project-Based Learning of an EPICS Class

In previous works, the perceived safety and comfort are currently not the principal objectives of all industries, especially robotics system. It might lead not to take psychological safety into con...

https://journals.sagepub.com/doi/pdf/10.1177/1687814020979430

Develop the socially human-aware navigation system using dynamic window approach and optimize cost function for autonomous medical robot:

In the actual industrial production process, the method of adaptively tuning proportional–integral–derivative (PID) parameters online by neural network can adapt to different characteristics of different controlled objects better than the controller with PID. However, the commonly used microcontroller unit (MCU) cannot meet the application scenarios of real time and high reliability. Therefore, in this paper, a closed-loop motion control system based on BP neural network (BPNN) PID controller by using a Xilinx field programmable gate array (FPGA) solution is proposed. In the design of the controller, it is divided into several sub-modules according to the modular design idea. The forward propagation module is used to complete the forward propagation operation from the input layer to the output layer. The PID module implements the mapping of PID arithmetic to register transfer level (RTL) and is responsible for completing the output of control amount. The main state machine module generates enable signals that control the sequential execution of each sub-module. The error backpropagation and weight update module completes the update of the weights of each layer of the network. The peripheral modules of the control system are divided into two main parts. The speed measurement module completes the acquisition of the output pulse signal of the encoder and the measurement of the motor speed. The pulse width modulation (PWM) signal generation module generates PWM waves with different duty cycles to control the rotation speed of the motor. A co-simulation of Modelsim and Simulink is used to simulate and verify the system, and a test analysis is also performed on the development platform. The results show that the proposed system can realize the self-tuning of PID control parameters, and also has the characteristics of reliable performance, high real-time performance, and strong anti-interference. Compared with MCU, the convergence speed is far more than three orders of magnitude, which proves its superiority.

/pdf/a-design-of-fpga-based-neural-network-pid-controller-for-39s1m3hw.pdf

A Design of FPGA-Based Neural Network PID Controller for Motion Control System

Most of quadcopter operate in the outdoor environment where is often complex and unpredicted. In order to control the quadcopter in unknown outdoor environment, it should be designed an excellent filter to estimate complete state vector which illustrates the movement of rigid body. In this paper, two filters such as Complementary and Kalman are investigated to compare the performance. Quadcopter collect only measurements from a low-cost inertial measurement unit, IMU-MPU6050. The raw data is put into filter to estimate the state vector in system. In the simulations, these filters are studied to implement in the model of quadrotor. Later, the hardware platform of quadcopter is built to denote experimental results in order to validate the effective design of Complementary filter and Kalman filter in quadcopter.

Experimental comparison of Complementary filter and Kalman filter design for low-cost sensor in quadcopter

In the industrial working area, it is complex to predict any problems such as lift up and down the delivered goods. It may lead to unstable movement while automated guided vehicle tracks the trajectory. In this research, the implementation of Fuzzy Inference System in AGV to stabilize the tracking error under various loads conditions. In the experiment, AGV operates in a real industrial condition with variation of loads. The results indicate that vehicle can work well regardless of the carried loads.

Using Fuzzy Logic Scheme for Automated Guided Vehicle To Track Following Path Under Various Load

Recent years, farming issue is one of the important problems and need to be considered. To handle this issue, it is so essential that we need figure out solutions to assure the growth of crops effectively. In this paper, we propose the new solution to plant automatically and monitor remotely. Firstly, the model of plantation is described in depth. Then, CPU plays a central role to handle the irrigation and aftercare the whole system. It is implemented several sensors and actuators to manipulate the environmental farm. The system parameters are updated in cloud frequently. Furthermore, all of plantations is supervised by digital cameras. The host PC will analyze the image to predict the process of development in agriculture. Therefore, via Internet of Things (IoT) and image processing technology, farmers are able to estimate the best harvesting time and assure the mass production of food.

Design of Green Agriculture System Using Internet of Things and Image Processing Techniques

This paper concerntrates on the analysis, design and control methodology in the machining servo system. The overall architecture of motion system is investigated to realize the drawbacks of traditional scheme. Then, this research proposes the suitable design of controller due to rapid calculation, high precision and friendly graphical user interface. The diagram of Fuzzy self-tuning PID and feedforward is constructed to drive the servo machine. The hardware platform of controller has been accomplised such as schematic, PCB artworks and soldering. Later, the middleware and firmware have been closed to promote the execution between controller and computer. The intelligent algorithm is embedded in board level by TMS320C6727 to overcome the problems, for example the existing nonlinear properties, external disturbances or servo lag phenomena. Based on the theoretical design, several simulation results are provided to verify the contributions. From the experimental performance, it can be seen clearly that this controller smoothly manipulate the servo motor, ensure real-time performance and high tracking position.

Experimental design of PC-based servo system

In the field of logistics, the storehouse management plays an important role. It is difficult to handle a large warehouse only with human. Therefore, the implementation of path tracking AGV robot is investigated as an automated solution. From the requirements of warehouse service, the hardware structure of robot is demonstrated in this work. Then, the software design is built to operate in real-time. Besides, overall system is scheduled to realize in various cases. The monitoring program in host PC will track the actual position of AGV along the trajectory. From the experimental design of AGV robot, the feasibility and capability of design and control approach which is proposed in this paper are proved.

Ha Quang Thinh Ngo

Papers

Experimental comparison of Complementary filter and Kalman filter design for low-cost sensor in quadcopter

Using Fuzzy Logic Scheme for Automated Guided Vehicle To Track Following Path Under Various Load

Design of Green Agriculture System Using Internet of Things and Image Processing Techniques

Experimental design of PC-based servo system

Research and Develop of AGV Platform for the Logistics Warehouse Environment