Real-Time Navigation, Guidance, and Control of a UAV Using Low-Cost Sensors

Author(s):  
Jong-Hyuk Kim ◽  
Salah Sukkarieh ◽  
Stuart Wishart
2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone

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.


2021 ◽  
Vol 2042 (1) ◽  
pp. 012114
Author(s):  
Dongjun Mah ◽  
Michael Kim ◽  
Athanasios Tzempelikos

Abstract The concept of integrating programmable low-cost cameras into the office infrastructure and BMS for real-time, web-based sensing and control of the luminous environment in buildings is presented in this study. Experiments were conducted to evaluate the potential of predicting the luminance field perceived by an office occupant using a programmable calibrated HDR camera installed at the rear side of a computer monitor or on the wall behind the occupant, for a variety of sky conditions and shading options. The generated luminance maps using Python scripts with OpenCV packages were further processed to extract daylighting and glare metrics using Evalgare. The results showed that: (i) among the different camera resolutions that were compared, the 330x330 resolution was selected as the best option to balance between accurate capturing of visual environment and comfort and computational efficiency; (ii) a camera sensor embedded on the rear side of a computer screen could capture interior visual conditions consistently similarly to those viewed by the occupant, except for sunny conditions without proper shading protection. This prototype study paves the way for luminance monitoring and daylight control using programmable low-cost camera sensors embedded into the office infrastructure.


2021 ◽  
Author(s):  
Lukas Spannagl ◽  
Elias Hampp ◽  
Andrea Carron ◽  
Jerome Sieber ◽  
Carlo Alberto Pascucci ◽  
...  

2018 ◽  
Vol 148 ◽  
pp. 175-185 ◽  
Author(s):  
Ying Chen ◽  
Zhen He ◽  
Ding Zhou ◽  
Zhenhua Yu ◽  
Shunli Li

This paper investigates a real time distributed controller for a 3 DOF delta robot using low-cost educational simple microcontrollers. The parallel computing technique is used were the computational load is divided among several microcontrollers networked to each other to implement control methods. More specifically, the computation is distributed among four microcontrollers (MCU’s) which are connected to each other using CAN bus protocol. The main MCU is used to compute the control law. Each of the remaining MCU’s is connected to one actuator and its attached encoder to form an Intelligent sensor-actuator system (ISAS). At each sample time, the ISAS broadcast a message using the CAN bus to the main MCU containing the information about the motor position. Then according to the control law, ISAS receives the corresponding controller value that has to be applied to the motor. All required periodic, aperiodic and sporadic tasks, were implemented and will be handled by these MCU’s. Using this design, the computation time of control law can be minimized and implemented using ARDUINO microcontrollers. More, this method increases the flexibility of the system for additional equipment and control by adding more nodes to the network. The results show the applicability of the proposed distributed controller, it can track different types of control signals with acceleration up to 9.8 m/s^2 (1g).


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