In this study, we design and verify an intake system using the wake of a pocket-sized quadcopter for the chemical plume tracing (CPT) problem. Solving CPT represents an important technique in the field of engineering because it can be used to perform rescue operations at the time of a disaster and to identify sources of harmful substances. An appropriate intake of air when sensing odors plays an important role in performing CPT. Hence, we used the air flow generated by a quadcopter itself to intake chemical particles into two alcohol sensors. By experimental evaluation, we verified that the quadcopter wake intake method has good directivity and can be used to realize CPT. Concretely, even at various odor source heights, the quadcopter had a three-dimensional CPT success rate of at least 70%. These results imply that, although a further development of three-dimensional CPT is necessary in order to conduct it in unknown and cluttered environments, the intake method proposed in this paper enables a pocket-sized quadcopter to perform three-dimensional CPT.
In this research, we aim to model an adaptive behavior of an animal and implement it to an autonomous robot. The conventional bio-inspired algorithm is difficult to demonstrate the ability as much as the animal because it models without considering dynamic characteristics of the robot. Therefore, in this study, we constructed an animal-in-the-loop system, which is a novel experimental system for identifying the adaptive behavior of the animal in a form that considers the dynamic characteristics of the robot to be implemented.
One of the problems when designing an aircraft is flight time estimation. When we design the aircraft, in general, calculating the maximum takeoff weight becomes the priority. The longer flight time required by the aircraft, the more batteries should be added. More batteries mean the payload capacity of the aircraft is decreased. On the other hand, adding more weight will increase the requirement of using more powerful motors. We need to take into our account, that using powerful motors should be calculated carefully because the current consumption is also increased. This problem is circling in the same situation, without any real solution to overcome the problem. As unmanned aircraft has become a critical part of human life for example in surveillance, agricultural, and medicine delivery mission, obtaining the optimum and efficient flight time is vital. In this research, we propose a novel approach of maximum takeoff weight calculation that is needed when designing the aircraft by looking at the complete map of motor specifications. The goal of this paper is to help any aircraft user from hobbyist to professional to determine whether their aircraft design is feasible.
The deployment of a group of robots equipped with sensors for monitoring, also known as a robotic sensor network, is a promising technological solution to solve time-critical societal and environmental issues. This paper considers the problem of deploying a robotic sensor network to persistently and effectively monitor multiple locations of interest in a large field represented by grids. To this end, we propose a novel two-layer control framework where the first layer (i.e., task allocation strategy) encapsulates the targeted grids into a set of tasks (small regions of interest) followed by optimally allocating the robots to each task based on their initial position (location of their base stations) and sensing capabilities. The second layer (i.e., persistent monitoring algorithm) generates each robot’s motion control input to ensure persistent monitoring over the designated region of interest. The proposed framework is demonstrated and evaluated via numerical simulations. It is shown that the proposed control framework improves real-time monitoring in terms of both the coverage performance and travel distance of the robots.
1 June 2023 in IAES International Journal of Artificial Intelligence (IJ-AI)
A novel metaheuristic optimization algorithm based on cuckoo search algorithm (CSA) is presented to solve the construction site layout planning problem (CSLP). CSLP is a complex optimization problem with various applications, such as plant layout, construction site layout, and computer chip layout. Many researchers have investigated the CSLP by applying many algorithms in an exact or heuristic approach. Although both methods yield a promising result, technically, nature-inspired algorithms demonstrate high achievement in successful percentage. In the last two decades, researchers have been developing a new nature-inspired algorithm for solving different types of optimization problems. The CSA has gained popularity in resolving large and complex issues with promising results compared with other nature-inspired algorithms. However, for solving CSLP, the algorithm based on CSA is still minor. Thus, this study proposed CSA with additional modification in the algorithm mechanism, where the algorithm shows a promising result and can solve CSLP cases.
30 April 2022 in Journal of ICT Research and Applications
The implementation of industrial revolution 4.0 in manufacturing industries is necessary to adapt to the rapid changes of technologies. The milling process is one of the common manufacturing processes applied in the industries to produce engineering products. The vibration that occurs in the milling process can disturb the continuity of the process. The wired vibration monitoring system implemented in the manufacturing process needs to be replaced with the wireless monitoring system. Hence wireless vibration monitoring system is developed to solve the problem with wired monitoring systems where tucked cable and high cost are the main challenges of the wired monitoring system. The wireless monitoring system setup is built using three components: sensor node, monitoring node, and base station. Milling experiments with various depths of cut, feed rate, and spindle speed were conducted to examine the performance of the wireless monitoring system. The results indicate the wireless system shows similar data recorded by the wired system. The wireless vibration monitoring system can identify the effect of milling parameters such as depth of cut, feed rate, and spindle speed on the vibrations level. The effect of cut depth is more significant than spindle speed and feed rate in the defined parameters.