Time-minimum motion handling of open liquid-filled objects using sparse sequential quadratic programming
- Authors: Le, Hieu , Appuhamillage, Gayan , Nguyen, Linh
- Date: 2023
- Type: Text , Conference paper
- Relation: 2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023, Sivas, Turkey, 11-13 October 2023, 2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023
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- Description: The paper presents an efficient approach to minimize motion time of an industrial robot so that it can successfully manipulate an open and liquid-filled object in pick-and-place operations. It is first proposed a motion planning optimization problem, where the total motion duration is considered as a cost function. Moreover, the robot physical limits such as its joint positions, velocities and accelerations are used as the optimization constrains. On the other hand, to ensure an open and liquidfilled object always upright, orientation constraints of the robot end-effector are taken into account. More specifically, roll and pitch of the end-effector are proposed to be fixed during the transportation, which ensures there is no tipping over in the object. The formulated motion planning optimization problem is then efficiently solved by using the sparse sequential quadratic programming method. Our approach excels in optimizing the motion trajectory by leveraging its flexibility, accommodating various trajectory shapes that satisfy the kinematic conditions. The optimization leads to more efficient and effective motion execution, resulting in a substantial reduction in the overall motion profile duration. Extensive evaluation of the proposed approach on a KUKA robot model demonstrates its effectiveness. © 2023 IEEE.
Agoraphilic navigation algorithm under dynamic environment
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Appuhamillage, Gayan , Choudhury, Tanveer
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE/ASME Transactions on Mechatronics Vol. 27, no. 3 (2022), p. 1727-1737
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- Description: This article presents a summary of the work done on the development of a new algorithm for mobile robot navigation in unknown dynamic environment. The developed humanlike algorithm uses a free-space attraction (Agoraphilic) concept for robot navigation. The algorithm presented in this article is an advanced development of the Agoraphilic navigation algorithm. The Agoraphilic algorithm does not look for obstacles (problems) to avoid but rather for free spaces toward the goal (solutions) to follow. The original Agoraphilic while it was able to overcome the limitations of the traditional algorithms had its own limitations in navigating robots in environments cluttered with moving obstacles. The new Agoraphilic Navigation Algorithm under Dynamic Environment (ANADE) was developed to overcome those limitations. ANADE consists of seven main modules reported in this article. The objects tracking and objects prediction methodologies developed for the algorithm estimate future growing free-space passages toward the goal. The algorithm generates a time-varying single attractive force to pull the robot through the free space toward the predicted (future) growing free-space passages leading to the goal. The new algorithm was tested, not only through simulation, but also through experimental work. Summary of the experimental results is presented and discussed in this article. © 1996-2012 IEEE.
Cybersecurity risks in meat processing plant and impacts on total productive maintenance
- Authors: Chundhoo, Vickram , Chattopadhyay, Gopinath , Karmakar, Gour , Appuhamillage, Gayan
- Date: 2021
- Type: Text , Conference paper
- Relation: 2021 International Conference on Maintenance and Intelligent Asset Management; ICMIAM 2021, Ballarat; 12-15 December 2021
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- Description: Technological changes have been happening in production facilities including food manufacturing industries in an ever-increasing rate. This includes advancement in data capture devices, signal processing, communication capabilities and automated process control systems such as Internet of Things. It is more challenging where production systems are highly reliant on automation and robotics. Remote performance monitoring and controls are becoming progressively vulnerable due to risks associated with cyber security and corporate espionage. May 2021 cyber-Attack forced JBS meats USA to pay 11m in ransom money to stop any further disruptions in services. This heavily impacted JBS global operations including JBS Australian food manufacturing facilities. Food production facilities in Australia have critical control points supported by smart technologies as part of their food safety management systems. Cyber-Attacks on production facilities could result in financial, operational, health and safety consequences. As survey by the Australian Cyber Security Centre in 2020 revealed that Australian small businesses are impacted by cybercime each year with a loss of 300m. To present the potential cyber security threats and their associated risk level, a case study is presented based on the processing and manufacture of meat products in Australia. From this case study, to protect the meat industries from attacks, we identify cyber security attacks and their possible mitigation strategies. This research shows cyber security attacks can severely affect Overall Equipment Effectiveness which motivate us to embed cyber security as an additional pillar in existing 8 pillars Total Productive Maintenance. If cyber security is added as additional pillar, it will improve the quality of end products and overall productivity of manufacturing industries. © 2021 IEEE.
Real-time concrete crack detection and instance segmentation using deep transfer learning
- Authors: Piyathilaka, Lasitha , Preethichandra, Daluwathu , Izhar, Umer , Appuhamillage, Gayan
- Date: 2020
- Type: Text , Journal article
- Relation: Engineering Proceedings Vol. 2, no. 1 (2020), p.
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- Description: Cracks on concrete infrastructure are one of the early indications of structural degradation which needs to be identified early as possible to carry out early preventive measures to avoid further damage. In this paper, we propose to use YOLACT: a real-time instance segmentation algorithm for automatic concrete crack detection. This deep learning algorithm is used with transfer learning to train the YOLACT network to identify and localize cracks with their corresponding masks which can be used to identify each crack instance. The transfer learning techniques allowed us to train the network on a relatively small dataset of 500 crack images. To train the YOLACT network, we created a dataset with ground-truth masks from images collected from publicly available datasets. We evaluated the trained YOLACT model for concrete crack detection with ResNet-50 and ResNet-101 backbone architectures for both precision and speed of detection. The trained model achieved high mAP results with real-time frame rates when tested on concrete crack images on a single GPU. The YOLACT algorithm was able to correctly segment multiple cracks with individual instance level masks with high localization accuracy.
Assessing transformer oil quality using deep convolutional networks
- Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
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- Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
- Description: E1
On the apex seal analysis of limaçon positive displacement machines
- Authors: Phung, Truong , Sultan, Ibrahim , Appuhamillage, Gayan
- Date: 2018
- Type: Text , Journal article
- Relation: Mechanism and Machine Theory Vol. 127, no. (2018), p. 126-145
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- Description: Rotary machines, and limaçon machines in particular, offer a better power to weight ratio compared to reciprocating machines; however, leakage due to improper apex and side sealing have prevented rotary machines from thriving. In this paper, a modelling approach is presented to analyse the vibration of apex seal during the machine operation and the power loss caused by the seal friction. The seal and spring are modelled as a spring-mass system in which the seal deformation is negligible. The seal-groove relative positions have then been categorised into nine different possible cases based on the number of contact points between the seal and the seal groove. A case study has been presented to demonstrate the reliability of the model.
Optimum grasp force and resistance to slippage
- Authors: Dzitac, Pavel , Mazid, Abdul Md , Ibrahim, Yousef , Choudhury, Tanveer , Appuhamillage, Gayan
- Date: 2017
- Type: Text , Conference paper
- Relation: 2017 IEEE International Conference on Mechatronics (ICM) p. 297-302
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- Description: This paper presents an analysis and experimental results as part of the research into the optimal rate of grasp force application in precision grasping. It also offers the concept of resistance to object rotation in the robot gripper, which in turn contributes to the resistance to object slippage during robotic object manipulation. It is envisaged that this knowledge will be useful to researchers and designers of robotic grippers, especially those for industrial applications.
Friction-based slip detection in robotic grasping
- Authors: Dzitac, Pavel , Mazid, Abdul Md , Ibrahim, Yousef , Appuhamillage, Gayan , Choudhury, Tanveer
- Date: 2015
- Type: Text , Conference paper
- Relation: IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society p. 004871-004874
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- Description: A functional prototype of a friction-based object slippage detection gripper for robotic grasping and manipulation has been designed and built. Object grasping and manipulation experiments have been successfully performed to study the appropriateness of the methodology and the newly built slippage detection gripper. The main advantage of this slippage detection method is that slippage detection is an inherent capability of the sensing element, and not a derived capability like that of sensors based on vibration. This slippage detection and control strategy is simple by design and low in cost, but robust in function. It has the potential to be used in a variety of environments such as high temperatures, low temperatures and underwater. The robustness of the design makes it highly suitable for grasping and manipulating safely a large range of object weights and sizes.
Friction-based slippage and tangential force detection in robotic grasping
- Authors: Dzitac, Pavel , Mazid, Abdul Md , Ibrahim, Yousef , Choudhury, Tanveer , Appuhamillage, Gayan
- Date: 2015
- Type: Text , Conference paper
- Relation: IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society p. 004871-004874
- Full Text: false
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- Description: This paper presents a newly developed parallel gripper prototype capable of sensing grasp force, tangential force and slippage. In this design the gripper itself is used as part of the sensing strategy rather than just being simply a structural support for other sensors. The sensing capability of this gripper is simple in design and reliable. The sensing strategy can be customised to specific applications such as the ability to handle large loads while maintaining its ability to detect slippage as reliably as when handling lighter loads.
Optimal sensing requirement for slippage prevention in robotic grasping
- Authors: Dzitac, Pavel , Mazid, Abdul Md , Ibrahim, Yousef , Appuhamillage, Gayan , Choudhury, Tanveer
- Date: 2015
- Type: Text , Conference proceedings
- Full Text: false
- Description: This paper presents a new theoretical development and modelling related to the requirement of the minimum number of sensors necessary for slippage prevention in robotic grasping. A fundamental experimental investigation has been conducted to support the newly developed postulate. A series of basic experiments proved that it is possible to evaluate the contributions of various sensors to slippage prevention and control in robotic grasping. The use of three discrete physical sensors, one for each of the three sensing functions (normal, tangential and slippage), has been proven to be the most reliable combination for slippage prevention in robotic grasping. It was also proven that the best performance from a two-sensor combination can be achieved when normal grasp force and tangential force are both monitored in the grasping process. © 2015 IEEE.