cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Iswanto
Contact Email
-
Phone
+628995023004
Journal Mail Official
jrc@umy.ac.id
Editorial Address
Kantor LP3M Gedung D Kampus Terpadu UMY Jl. Brawijaya, Kasihan, Bantul, Yogyakarta 55183
Location
Kab. bantul,
Daerah istimewa yogyakarta
INDONESIA
Journal of Robotics and Control (JRC)
Published by Universitas Muhammadiyah Yogyakarta
ISSN : 27155056     EISSN : 27155072     DOI : https://doi.org/10.18196/jrc
Core Subject : Science, Engineering,
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering
Journal of Robotics and Control (JRC) is an international open-access journal published by Universitas Muhammadiyah Yogyakarta. The journal invites students, researchers, and engineers to contribute to the development of theoretical and practice-oriented theories of Robotics and Control. Its scope includes (but not limited) to the following: Manipulator Robot, Mobile Robot, Flying Robot, Autonomous Robot, Automation Control, Programmable Logic Controller (PLC), SCADA, DCS, Wonderware, Industrial Robot, Robot Controller, Classical Control, Modern Control, Feedback Control, PID Controller, Fuzzy Logic Controller, State Feedback Controller, Neural Network Control, Linear Control, Optimal Control, Nonlinear Control, Robust Control, Adaptive Control, Geometry Control, Visual Control, Tracking Control, Artificial Intelligence, Power Electronic Control System, Grid Control, DC-DC Converter Control, Embedded Intelligence, Network Control System, Automatic Control and etc.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 15 Documents
 1   2 
Search results for , issue "Vol 4, No 3 (2023)" : 15 Documents clear
Energy Consumption Minimization for Autonomous Mobile Robot: A Convex Approximation Approach Van, Nguyen Thi Thanh; Tien, Ngo Manh; Luong, Nguyen Cong; Duyen, Ha Thi Kim
Journal of Robotics and Control (JRC) Vol 4, No 3 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i3.17509

Abstract

In this paper, we consider a trajectory design problem of an autonomous mobile robot working in industrial environments. In particular, we formulate an optimization problem that jointly determines the trajectory of the robot and the time step duration to minimize the energy consumption without obstacle collisions. We consider both static and moving obstacles scenarios. The optimization problems are nonconvex, and the main contribution of this work proposing successive convex approximation (SCA) algorithms to solve the nonconvex problems with the presence of both static and moving obstacles. In particular, we first consider the optimization problem in the scenario with static obstacles and then consider the optimization problem in the scenario with static and moving obstacles. Then, we propose two SCA algorithms to solve the nonconvex optimization problems in both the scenarios. Simulation results clearly show that the proposed algorithms outperform the A* algorithm, in terms of energy consumption. This shows the effectiveness of the proposed algorithms.
Application of Odometry and Dijkstra Algorithm as Navigation and Shortest Path Determination System of Warehouse Mobile Robot Ubaidillah, Achmad; Sukri, Hanifudin
Journal of Robotics and Control (JRC) Vol 4, No 3 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i3.18489

Abstract

One of the technologies in the industrial world that utilizes robots is the delivery of goods in warehouses, especially in the goods distribution process. This is very useful, especially in terms of resource efficiency and reducing human error. The existing system in this process usually uses the line follower concept on the robot's path with a camera sensor to determine the destination location. If the line and destination are not detected by the sensor or camera, the robot's navigation system will experience an error. it can happen if the sensor is dirty or the track is faded. The aim of this research is to develop a robot navigation system for efficient goods delivery in warehouses by integrating odometry and Dijkstra's algorithm for path planning. Holonomic robot is a robot that moves freely without changing direction to produce motion with high mobility. Dijkstra's algorithm is added to the holonomic robot to obtain the fastest trajectory. by calculating the distance of the node that has not been passed from the initial position, if in the calculation the algorithm finds a shorter distance it will be stored as a new route replacing the previously recorded route. the distance traversed by the djikstra algorithm is 780 mm while a distance of 1100 mm obtains the other routes. The time for using the Djikstra method is proven to be 5.3 seconds faster than the track without the Djikstra method with the same speed. Uneven track terrain can result in a shift in the robot's position so that it can affect the travel data. The conclusion is that odometry and Dijkstra's algorithm as a planning system and finding the shortest path are very efficient for warehouse robots to deliver goods than ordinary line followers without Dijkstra, both in terms of distance and travel time.
A Novel Variable Stiffness Compound Extensor-Pneumatic Artificial Muscle (CE-PAM): Design and Mathematical Model Al-Mayahi, Wafaa; Al-Fahaam, Hassanin
Journal of Robotics and Control (JRC) Vol 4, No 3 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i3.18225

Abstract

Pneumatic artificial muscles (PAMs) have been exploited in robots utilized in various fields, including industry and medicine, due to their numerous advantages, such as their light weight; smooth, fast responses; and ability to generate significant force when fully extended. The actuator’s stiffness is important in these applications, and extensor PAMs (EPAMs) have a lower stiffness when compared to contractor PAMs (CPAMs). Because of this, this research presents the compound extensor PAM (CE-PAM), which is a novel actuator that has higher stiffness and can alter its stiffness at a fixed length or maintain a fixed stiffness at a variable length. This makes it useful in applications such as surgery robots and wearable robots. The CE-PAM is created by inserting the CPAM into the EPAM. Then, a mathematical model is developed to calculate the output force using several mathematical equations that relate the force, actuator size, and applied pressure to each other. The force is also calculated experimentally, and when comparing the mathematical with the experimental results, the error percentage appears greater than 20%. So the mathematical model is enhanced by calculating the wasted energy consumed by the actuator before the start of the bladder’s expansion, at which the force is zero because the pressure is consumed only for bladder expansion to touch the sleeve. The effect of the bladder’s thickness is calculated to further enhance the model by calculating the volume of air entering the muscle rather than the total muscle volume. To illustrate the effect of thickness on the actuator, experiments are conducted on CPAMs made of the same bladder material but with different thicknesses. A balloon is used in the manufacture of the bladder. Because it is a lightweight, thin material with a low thickness, it requires very low pressure to expand.
Multi Cost Function Fuzzy Stereo Matching Algorithm for Object Detection and Robot Motion Control Shetty, Akhil Appu; Hegde, Navya Thirumaleshwar; Vaz, Aldrin Claytus; Srinivasan, C R
Journal of Robotics and Control (JRC) Vol 4, No 3 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i3.17041

Abstract

Stereo matching algorithms work with multiple images of a scene, taken from two viewpoints, to generate depth information. Authors usually use a single matching function to generate similarity between corresponding regions in the images. In the present research, the authors have considered a combination of multiple data costs for disparity generation. Disparity maps generated from stereo images tend to have noisy sections. The presented research work is related to a methodology to refine such disparity maps such that they can be further processed to detect obstacle regions.  A novel entropy based selective refinement (ESR) technique is proposed to refine the initial disparity map. The information from both the left disparity and right disparity maps are used for this refinement technique. For every disparity map, block wise entropy is calculated. The average entropy values of the corresponding positions in the disparity maps are compared. If the variation between these entropy values exceeds a threshold, then the corresponding disparity value is replaced with the mean disparity of the block with lower entropy. The results of this refinement are compared with similar methods and was observed to be better. Furthermore, in this research work, the v-disparity values are used to highlight the road surface in the disparity map. The regions belonging to the sky are removed through HSV based segmentation. The remaining regions which are our ROIs, are refined through a u-disparity area-based technique.  Based on this, the closest obstacles are detected through the use of k-means segmentation.  The segmented regions are further refined through a u-disparity image information-based technique and used as masks to highlight obstacle regions in the disparity maps. This information is used in conjunction with a kalman filter based path planning algorithm to guide a mobile robot from a source location to a destination location while also avoiding any obstacle detected in its path. A stereo camera setup was built and the performance of the algorithm on local real-life images, captured through the cameras, was observed. The evaluation of the proposed methodologies was carried out using real life out door images obtained from KITTI dataset and images with radiometric variations from Middlebury stereo dataset.
An Ultra Fast Semantic Segmentation Model for AMR’s Path Planning Tran, Hoai-Linh; Dang, Thai-Viet
Journal of Robotics and Control (JRC) Vol 4, No 3 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i3.18758

Abstract

Computer vision plays a significant role in mobile robot navigation due to the abundance of information extracted from digital images. On the basis of the captured images, mobile robots determine their location and proceed to the desired destination. Obstacle avoidance still requires a complex sensor system with a high computational efficiency requirement due to the complexity of the environment. This research provides a real-time solution to the issue of extracting corridor scenes from a single image. Using an ultra-fast semantic segmentation model to reduce the number of training parameters and the cost of computation. In addition, the mean Intersection over Union (mIoU) is 89%, and the high accuracy is 95%. To demonstrate the viability of the prosed method, the simulation results are contrasted to those of contemporary techniques. Finally, the authors employ the segmented image to construct the frontal view of the mobile robot in order to determine the available free areas for mobile robot path planning tasks.

Page 2 of 2 | Total Record : 15

 1   2 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol. 6 No. 5 (2025) Vol. 6 No. 4 (2025) Vol. 6 No. 2 (2025) Vol. 6 No. 1 (2025) Vol 5, No 6 (2024) Vol. 5 No. 6 (2024) Vol. 5 No. 5 (2024) Vol 5, No 5 (2024) Vol 5, No 4 (2024) Vol 5, No 3 (2024) Vol 5, No 2 (2024) Vol 5, No 1 (2024) Vol 4, No 6 (2023) Vol 4, No 5 (2023) Vol 4, No 4 (2023) Vol 4, No 3 (2023) Vol 4, No 2 (2023) Vol 4, No 1 (2023) Vol 3, No 6 (2022): November Vol 3, No 5 (2022): September Vol 3, No 4 (2022): July Vol 3, No 3 (2022): May Vol 3, No 2 (2022): March Vol 3, No 1 (2022): January Vol 2, No 6 (2021): November (Forthcoming Issue) Vol 2, No 6 (2021): November Vol 2, No 5 (2021): September Vol 2, No 5 (2021): September (Forthcoming Issue) Vol 2, No 4 (2021): July (Forthcoming Issue) Vol 2, No 4 (2021): July Vol 2, No 3 (2021): May Vol 2, No 3 (2021): May (Forthcoming Issue) Vol 2, No 2 (2021): March Vol 2, No 2 (2021): March (Forthcoming Issue) Vol 2, No 1 (2021): January Vol 1, No 6 (2020): November Vol 1, No 5 (2020): September Vol 1, No 4 (2020): July Vol 1, No 3 (2020): May Vol 1, No 2 (2020): March Vol 1, No 1 (2020): January More Issue