Abstract

Realistic physics engines play a crucial role for learning to manipulate deformable objects such as garments in simulation. By doing so, researchers can circumvent challenges such as sensing the deformation of the object in the real-world. In spite of the extensive use of simulations for this task, few works have evaluated the reality gap between deformable object simulators and real-world data. We present a benchmark dataset to evaluate the sim-to-real gap in cloth manipulation. The dataset is collected by performing a dynamic cloth manipulation task involving contact with a rigid table. We use the dataset to evaluate the reality gap, computational time, and simulation stability of four popular deformable object simulators: MuJoCo, Bullet, Flex, and SOFA. Additionally, we discuss the benefits and drawbacks of each simulator.

>Project Website<

Keywords

• Datasets for Robot Learning
• Bimanual Manipulation
• Deformable Object Manipulation

BibTeX

@article{blanco2024benchmarking,
  title={Benchmarking the sim-to-real gap in cloth manipulation},
  author={Blanco-Mulero, David and Barbany, Oriol and Alcan, Gokhan and Colom{\'e}, Adri{\`a} and Torras, Carme and Kyrki, Ville},
  journal={IEEE Robotics and Automation Letters},
  volume={9}, 
  number={3}, 
  pages={1760--1767},
  year={2024},
  publisher={IEEE}
}

Abstract

In this paper, optimization-oriented high fidelity indicated torque models which cover the whole operating regions under both steady-state and transient cycles for heavy-duty vehicles are developed. Two different experiments are performed and their data are merged to be utilized in the training of the models. In the first experiment, all combustion input channels are excited by quadratic chirp signals with different sweeps in their frequency profiles. Different from the first experiment, the engine speed is excited by ramp-hold signals in the second experiment. The estimations of friction, pumping and inertia torques in addition to the torque measured from the engine dynamometer are utilized in the indicated torque calculations. In order to model the calculated indicated torque, a nonlinear finite impulse response (NFIR) model with a single layer sigmoid neural network has been designed. A sensitivity analysis is performed by generating several models with different number of input regressors and neurons. Experimental results show that the majority of the models in a selected wide range of the model parameters are validated with fit accuracies higher than 90 % and 85 % on the World Harmonized Stationary Cycle (WHSC) and the World Harmonic Transient Cycle (WHTC), respectively.

Keywords

• • Diesel engine
  • Indicated torque
  • System identification
  • Experiment design
  • NFIR model

BibTeX

@article{alcan2020optimization,
  title={Optimization-oriented high fidelity NFIR models for estimating indicated torque in diesel engines},
  author={Alcan, Gokhan and Aran, Volkan and Unel, Mustafa and Yilmaz, Metin and Gurel, Cetin and Koprubasi, Kerem},
  journal={International Journal of Automotive Technology},
  volume={21},
  number={3},
  pages={729--737},
  year={2020},
  publisher={The Korean Society of Automotive Engineers}
}

Abstract

In this work, acceleration feedback is utilized in a hierarchical control structure for robust trajectory control of a quadrotor helicopter subject to external disturbances where reference attitude angles are determined through a nonlinear optimization algorithm. Furthermore, an acceleration-based disturbance observer (AbDOB) is designed to estimate disturbances acting on the positional dynamics of the quadrotor. For the attitude control, nested position, velocity, and inner acceleration feedback loops consisting of PID and PI type controllers are developed to provide high stiffness against external disturbances. Reliable angular acceleration is estimated through a cascaded filter structure. Simulation results show that the proposed controllers provide robust trajectory tracking performance when the aerial vehicle is subject to wind gusts generated by the Dryden wind model along with the uncertainties and measurement noise. Results also demonstrate that the reference attitude angles calculated through nonlinear optimization are smooth and within the desired bounds.

Keywords

• Robust Control
• Acceleration Feedback
• Disturbance Observer
• Quadrotor
• Hierarchical Control
• Nonlinear Optimization

BibTeX

@article{zaki2019robust,
  title={Robust trajectory control of an unmanned aerial vehicle using acceleration feedback},
  author={Zaki, Hammad and Alcan, Gokhan and Unel, Mustafa},
  journal={International Journal of Mechatronics and Manufacturing Systems},
  volume={12},
  number={3-4},
  pages={298--317},
  year={2019},
  publisher={Inderscience Publishers (IEL)}
}

Abstract

Diesel engines are still widely used in heavy-duty engine industry because of their high energy conversion efficiency. In recent decades, governmental institutions limit the maximum acceptable hazardous emissions of diesel engines by stringent international regulations, which enforces engine manufacturers to find a solution for reducing the emissions while keeping the power requirements. A reliable model of the diesel engine combustion process can be quite useful to search for the best engine operating conditions. In this study, nonlinear modeling of a heavy-duty diesel engine NOx emission formation is presented. As a new experiment design, air-path and fuel-path input channels were excited by chirp signals where the frequency profile of each channel is different in terms of the number and the direction of the sweeps. This method is proposed as an alternative to the steady-state experiment design based modeling approach to substantially reduce testing time and improve modeling accuracy in transient operating conditions. Sigmoid based nonlinear autoregressive with exogenous input (NARX) model is employed to predict NOx emissions with given input set under both steady-state and transient cycles. Models for different values of parameters are generated to analyze the sensitivity to parameter changes and a parameter selection method using an easy-to-interpret map is proposed to find the best modeling parameters. Experimental results show that the steady-state and the transient validation accuracies for the majority of the obtained models are higher than 80% and 70%, respectively.

Highlights

• Data-driven modeling of diesel engine NOx emissions using sigmoid NARX model.
• A new design of experiments which include both chirp and ramp-hold signals.
• Reduction of testing time and improved modeling accuracy in transient cycle.
• An easy-to-interpret map as a convenient means for suitable parameter selection.
• Higher than 80% and 70% steady-state and transient validation accuracies.

Keywords

• Diesel engine
• Combustion process
• NOx emissions
• Experiment design
• Sigmoid NARX model

BibTeX

@article{alcan2019predicting,
  title={Predicting NOx emissions in diesel engines via sigmoid NARX models using a new experiment design for combustion identification},
  author={Alcan, Gokhan and Unel, Mustafa and Aran, Volkan and Yilmaz, Metin and Gurel, Cetin and Koprubasi, Kerem},
  journal={Measurement},
  volume={137},
  pages={71--81},
  year={2019},
  publisher={Elsevier}
}

Abstract

This study presents a biomedical device prototype based on small scale hydrodynamic cavitation. The application of small scale hydrodynamic cavitation and its integration to a biomedical device prototype is offered as an important alternative to other techniques, such as ultrasound therapy, and thus constitutes a local, cheap, and energy-efficient solution, for urinary stone therapy and abnormal tissue ablation (e.g., benign prostate hyperplasia (BPH)). The destructive nature of bubbly, cavitating, flows was exploited, and the potential of the prototype was assessed and characterized. Bubbles generated in a small flow restrictive element (micro-orifice) based on hydrodynamic cavitation were utilized for this purpose. The small bubbly, cavitating, flow generator (micro-orifice) was fitted to a small flexible probe, which was actuated with a micromanipulator using fine control. This probe also houses an imaging device for visualization so that the emerging cavitating flow could be locally targeted to the desired spot. In this study, the feasibility of this alternative treatment method and its integration to a device prototype were successfully accomplished.

BibTeX

@article{ghorbani2018biomedical,
  title={Biomedical device prototype based on small scale hydrodynamic cavitation},
  author={Ghorbani, Morteza and Sozer, Canberk and Alcan, Gokhan and Unel, Mustafa and Ekici, Sinan and Uvet, Huseyin and Kosar, Ali},
  journal={AIP Advances},
  volume={8},
  number={3},
  pages={035108},
  year={2018},
  publisher={AIP Publishing}
}

Abstract

In this study, spray formation and atomization, droplet evolutions, break-up, and corresponding cavitating flows at the outlet of a short micro-channel with an inner diameter of 152 μm were experimentally studied at different injection pressures with the use of a high speed visualization system. High speed visualization was performed at five different segments to cover a ∼27.5 mm distance beginning from the micro-channel outlet (Five segments, at distances of 0-5.5, 5.5-11, 11-16.5, 16.5-22 and 22-27.5 mm from the micro-channel outlet) to assess the spray formation mechanism. High speed visualization revealed that droplet evolution is initiated from the second segment at low upstream pressures (5-30 bars), whereas droplets are discretized from the liquid jet in the fourth and fifth segments at medium and high upstream pressures (40-100 bars). Bigger size droplets formed at the outlet up to an injection pressure of 30 bars, while cavitation effect of intensified cavitating flows became dominant beyond this injection pressure, leading to smaller droplet sizes and a more conical spray. Pressure drop was correlated together with Martinelli parameter for cavitating flows and a new correlation for two-phase pressure drop was developed. Moreover, in order to segment the discretized droplets at low upstream pressure (5-30 bars) from captured images and to perform an in-depth analysis on them, an active contour approach utilizing curve evolution and level set formulation was implemented. As shown by experimental results, droplets were successfully segmented at different low pressure levels. The droplet/bubble evolution can be exploited in biomedical and engineering applications, where destructive effects of bubbly cavitating flows are needed.

Highlights

• Spray formation in different segments starting from the outlet of a short microchannel was studied.
• An edge-free active contour method was implemented to successfully segment individual droplets.
• This study helps to visualize the formation of spray and to capture separated droplets in micro scale.
• A new correlation for predicting two-phase pressure drop was developed.

Keywords

• Micro scale cavitation
• Active contour
• Segmentation
• Spray
• Pressure drop correlation

BibTeX

@article{ghorbani2018characterization,
  title={Characterization and pressure drop correlation for sprays under the effect of micro scale cavitation},
  author={Ghorbani, Morteza and Alcan, Gokhan and Sadaghiani, Abdolali Khalili and Mohammadi, Ali and Unel, Mustafa and Gozuacik, Devrim and Ko{\c{s}}ar, Ali},
  journal={Experimental Thermal and Fluid Science},
  volume={91},
  pages={89--102},
  year={2018},
  publisher={Elsevier}
}

Abstract

Recent studies show the destructive effect of the energy released from the collapse of cavitation bubbles, which are generated in micro domains, on the targeted surfaces. The cavitation phenomenon occurs at low local pressures within flow restrictive elements and strongly affects fluid flow regimes inside microchannels which results in spray formation. Extended cavitation bubbles toward the outlet of the microchannel, droplet evolution, and spray breakup are among crucial mechanisms to be considered in spray structure. In this study, various spray structures under the effect of hydrodynamic cavitation were recorded using a high speed visualization system. Acquired images were analyzed and characterized using several image processing algorithms. In this regard, the fluid flow with ascending upstream pressures from 10 to 120 bar were passed through a microchannel with an inner diameter of 0.152 mm. The spray at the outlet of the microchannel was analyzed for these pressures in four different segments. Particle Shadow Sizing (PSS) imaging and several image processing techniques such as contrast stretching, thresholding and morphological operations were employed to identify the flow regimes in the separated segments. In addition, a vision based estimation technique that utilizes a Kalman filter was developed to estimate cone angle of the spray. Furthermore, classification of fluid flow regimes and morphological characteristics of the spray structure were outlined based on the cavitation number.

Highlights

• A complete system including generation of microscale cavitating flows was constructed.
• High speed visualization and novel image based analysis of spray structure were performed.
• High speed flow characterization and elimination of manual adjustments are the advantages of the proposed system.
• The fluid flow was classified as discrete droplet flow, liquid jet, jet cavitation, bubbly flow and highly vaporous bubbly flow.
• Obtained cone angle of multiphase flow was estimated through 3D Gaussian modeling and by employing a Kalman filter.

Keywords

• Cavitation
• Cone angle
• Kalman filter
• Microchannel
• Spray
• Visualization

BibTeX

@article{ghorbani2016visualization,
  title={Visualization of microscale cavitating flow regimes via particle shadow sizing imaging and vision based estimation of the cone angle},
  author={Ghorbani, Morteza and Alcan, Gokhan and Unel, Mustafa and Gozuacik, Devrim and Ekici, Sinan and Uvet, Huseyin and Sabanovic, Asif and Kosar, Ali},
  journal={Experimental Thermal and Fluid Science},
  volume={78},
  pages={322--333},
  year={2016},
  publisher={Elsevier}
}