Publications

@article{yang2022,
title = {Online Model Learning for Shape Control of Deformable Linear Objects},
author = {Yuxuan Yang and Johannes A. Stork and Todor Stoyanov},
url = {https://ieeexplore.ieee.org/document/9981080},
doi = {10.1109/IROS47612.2022.9981080},
year = {2022},
date = {2022-12-26},
journal = {2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages = {4056-4062},
abstract = {Traditional approaches to manipulating the state of deformable linear objects (DLOs) - i.e., cables, ropes - rely on model-based planning. However, constructing an accurate dynamic model of a DLO is challenging due to the complexity of interactions and a high number of degrees of freedom. This renders the task of achieving a desired DLO shape particularly difficult and motivates the use of model-free alternatives, which while maintaining generality suffer from a high sample complexity. In this paper, we bridge the gap between these fundamentally different approaches and propose a framework that learns dynamic models of DLOs through trial-and-error interaction. Akin to model-based reinforcement learning (RL), we interleave learning and exploration to solve a 3D shape control task for a DLO. Our approach requires only a fraction of the interaction samples of the current state-of-the-art model-free RL alternatives to achieve superior shape control performance. Unlike offline model learning, our approach does not require expert knowledge for data collection, retains the ability to explore, and automatically selects relevant experience.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{cosgunimpact,
title = {Impact-aware dual-arm grasping through time-invariant reference spreading},
author = {Cosgun, A and van Steen},
url = {https://pure.tue.nl/ws/portalfiles/portal/224201404/1020574_Impact_aware_grasping_through_time_invariant_reference_spreading.pdf},
year = {2022},
date = {2022-10-01},
abstract = {Eindhoven University of Technology},
abstract = {In robotic applications which involve handling objects or interaction with the environment,
robots generally establish contact at near-zero speed due to the effect of impacts. At impact, rapid velocity changes occur in the robot joints accompanied by large contact forces,
which can cause damage to the robot, humans, or the environment. As a result, robots
typically accelerate and decelerate repeatedly to achieve a task that involves contact, which
negatively affects the energy consumption and throughput. In order to increase the performance, control strategies are proposed that take into account the impact dynamics, which
are referred to as impact-aware control. Impact-aware control strategies exploit impacts, to
increase the swiftness of the performed tasks and reach a more human-like behavior. One
of the challenges in impact-aware control strategies is that, in presence of uncertainties, a
robot can experience an impact at a different time than expected. This causes the actual
state of the system to reside in a different mode than prescribed by the time-based reference
trajectory, which can cause the robot to compensate aggressively and possibly becoming unstable. Furthermore, when contact is expected to be established at multiple contact points
simultaneously, the controller can enter an unspecified and typically unpredictable mode.
Lastly, in case of external perturbations, the robot can lag behind compared to its reference
state at that time instant, which would cause the robot to “catch up” in order to reach its
desired state, which would generally be undesired.

The combination of a time-invariant control strategies and an impact-aware reference spreading control strategy can provide a possible solution for these challenges. By employing a reference that is solely a function of the robot’s position and orientation, and extending it around
an expected impact position, robots can be controlled towards an intentional impact in the
presence of uncertainties. Therefore, the goal of this project is to design an impact-aware
time-invariant reference spreading control strategy for a dual-arm robotic system capable
of swift grasping. To achieve this, a procedure is proposed to generate time-invariant references that can steer the robots towards a desired position and speed to swiftly grasp an
object, while ensuring the reference is compatible through the impact dynamics. In order
to be applicable on a dual-arm robotic system, the time-invariant reference spreading control strategy is cast into a task-based quadratic-programming control framework, which is
a common framework for control of complex systems. Furthermore, an intermediate mode
control strategy is proposed to ensure full contact is established when a loss of simultaneity
occurs. Additionally, a synchronization strategy is formulated to ensure the robots reach
the object at the same time. Finally, the effectiveness of the proposed control approach is
validated by means of numerical simulation studies on a two-dimensional, and a more complex three-dimensional scenario, which consists of a realistic seven degrees of freedom robot
setup.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{ozdemir2022development,
title = {Development of a virtual teaching environment with Algodoo:‘eye’and ‘cactus type light source’models},
author = {Özdemir, Erdougan and Coramik, Mustafa},
url = {https://iopscience.iop.org/article/10.1088/1361-6552/ac60b0/pdf},
year = {2022},
date = {2022-05-01},
journal = {Physics Education},
volume = {57},
number = {4},
pages = {045022},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{Cao2022,
title = {NEPTUNE: Non-Entangling Planning for Multiple Tethered Unmanned Vehicles},
author = {Cao, Muqing and Cao, Kun and Yuan, Shenghai and Nguyen, Thien-Minh and Xie, Lihua},
url = {https://arxiv.org/abs/2212.01536
https://arxiv.org/pdf/2212.01536},
year = {2022},
date = {2022-04-01},
journal = {arxiv:2212.01536},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{wallin2022,
title = {Learning multiobjective rough terrain traversability},
author = {Wallin, E. and Wiberg, V. and Vesterlund, F. and Holmgren, J. and Persson, H. and Servin, M.},
url = {https://authors.elsevier.com/sd/article/S0022489822000313
https://www.sciencedirect.com/science/article/pii/S0022489822000313/pdfft?md5=5dda8fdd1e395ea0e205c16deda5aed4&pid=1-s2.0-S0022489822000313-main.pdf
https://arxiv.org/pdf/2203.16354.pdf},
doi = {10.1016/j.jterra.2022.04.002 },
year = {2022},
date = {2022-04-01},
journal = {Journal of Terramechanics},
volume = {102},
pages = {17-26},
abstract = {We present a method that uses high-resolution topography data of rough terrain and ground vehicle simulation to predict traversability. Traversability is expressed as three independent measures: the ability to traverse the terrain at a target speed, energy consumption, and acceleration. The measures are continuous and reflect different objectives for planning that go beyond binary classification. A deep neural network is trained to predict the traversability measures from the local heightmap and target speed. To produce training data, we use an articulated vehicle with wheeled bogie suspensions and procedurally generated terrains. We evaluate the model on laser-scanned forest terrains, previously unseen by the model. The model predicts traversability with an accuracy of 90%. Predictions rely on features from the high-dimensional terrain data that surpass local roughness and slope relative to the heading. Correlations show that the three traversability measures are complementary to each other. With an inference speed 3000 times faster than the ground truth simulation and trivially parallelizable, the model is well suited for traversability analysis and optimal route planning over large areas.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{Song2022,
title = {Autonomous Wheel Loader Trajectory Tracking Control Using LPV-MPC},
author = {Song, Ruitao and Ye, Zhixian and Wang, Liyang and He, Tianyi and Zhang, Liangjun},
url = {https://arxiv.org/abs/2203.08944
https://youtu.be/QbNfS_wZKKA},
doi = {https://doi.org/10.48550/arxiv.2203.08944},
year = {2022},
date = {2022-03-30},
journal = {arxiv:2203.08944},
abstract = {In this paper, we present a systematic approach for high-performance and efficient trajectory tracking control of autonomous wheel loaders. With the nonlinear dynamic model of a wheel loader, nonlinear model predictive control (MPC) is used in offline trajectory planning to obtain a high-performance state-control trajectory while satisfying the state and control constraints. In tracking control, the nonlinear model is embedded into a Linear Parameter Varying (LPV) model and the LPV-MPC strategy is used to achieve fast online computation and good tracking performance. To demonstrate the effectiveness and the advantages of the LPV-MPC, we test and compare three model predictive control strategies in the high-fidelity simulation environment. With the planned trajectory, three tracking control strategies LPV-MPC, nonlinear MPC, and LTI-MPC are simulated and compared in the perspectives of computational burden and tracking performance. The LPV-MPC can achieve better performance than conventional LTI-MPC because more accurate nominal system dynamics are captured in the LPV model. In addition, LPV-MPC achieves slightly worse tracking performance but tremendously improved computational efficiency than nonlinear MPC. A video with loading cycles completed by our autonomous wheel loader in the simulation environment can be found here: this https URL.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{Urek2022,
title = {A Suggestion and Evaluation of a STEM Activity about Friction Coefficient for Pre-Service Science Teachers},
author = {Handan Ürek and Mustafa Çoramik},
url = {https://dergipark.org.tr/en/pub/jcer/issue/69325/1063301
https://dergipark.org.tr/en/download/article-file/2214073},
doi = {10.18009/jcer.1063301},
year = {2022},
date = {2022-01-02},
journal = {Journal of Computer and Education Research},
volume = {10},
number = {19},
pages = {202 - 235},
abstract = {In this study, the process of developing and evaluating a STEM activity which can be implemented during Science Teaching Laboratory Practice course in accordance with the 5E Model related to the concept of friction coefficient was addressed. The implementation of the activity was conducted in the form of a case study with the participation of 16 third year pre-service science teachers. Student journal forms and worksheets were utilized for the evaluation of the activity. As a result, it was determined that planned activity could be successfully applied to the pre-service teachers during the weekly course hours of Science Teaching Laboratory Practice course. In addition, positive feedbacks were obtained from pre-service teachers’ evaluation for the activity. It is believed that such studies, which establish connections between science and different disciplines, can contribute to the training of qualified science teachers and that such studies should be given more space in science teacher education.

},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{Özdemir2022,
title = {Development of a virtual teaching environment with Algodoo: eye and cactus type light source models},
author = {Erdoğan Özdemir
Coramik Mustafa},
url = {https://iopscience.iop.org/article/10.1088/1361-6552/ac60b0
https://iopscience.iop.org/article/10.1088/1361-6552/ac60b0/pdf?casa_token=V8xrPx7vhDAAAAAA:rPLZ6ro88reQ4VsHcF3r17FcMFZS5zgzLEr7VJMegEl3W8ni7Xy9hDyRQKmWdtQBQqQDDVQR},
doi = {10.1088/1361-6552/ac60b0},
year = {2022},
date = {2022-01-01},
journal = {Physics Education},
volume = {57},
number = {4},
pages = {045022},
abstract = {It is often necessary to enrich the teaching environment in order for students to learn optics in depth and to interpret the real optical situations with the information they have learned. In this study, a virtual teaching environment was developed using by Algodoo, a 2D simulation software. An eye model was created in order to explain the formation of the image in the eye in the teaching environment. Also, a cactus type light source model has also been developed to demonstrate that the image can be created in optics by using rays other than special rays. In order to show the success of the virtual teaching environment in modelling, previously known situations that the students had difficulty in understanding were simulated. Finally, some suggestions were made about the use of the virtual teaching environment. },
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{selby2021learning,
title = {Learning of Causal Observable Functions for Koopman-DFL Lifting Linearization of Nonlinear Controlled Systems and Its Application to Excavation Automation},
author = {Nicholas S Selby and Harry H Asada},
url = {https://arxiv.org/abs/2104.02004
https://arxiv.org/pdf/2104.02004
},
doi = {https://doi.org/10.1109/LRA.2021.3092256},
year = {2021},
date = {2021-06-01},
journal = {IEEE Robotics and Automation Letters},
volume = {6},
number = {4},
pages = {6297 - 6304},
abstract = {Effective and causal observable functions for low-order lifting linearization of nonlinear controlled systems are learned from data by using neural networks. While Koopman operator theory allows us to represent a nonlinear system as a linear system in an infinite-dimensional space of observables, exact linearization is guaranteed only for autonomous systems with no input, and finding effective observable functions for approximation with a low-order linear system remains an open question. Dual-Faceted Linearization uses a set of effective observables for low-order lifting linearization, but the method requires knowledge of the physical structure of the nonlinear system. Here, a data-driven method is presented for generating a set of nonlinear observable functions that can accurately approximate a nonlinear control system to a low-order linear control system. A caveat in using data of measured variables as observables is that the measured variables may contain input to the system, which incurs a causality contradiction when lifting the system, i.e., taking derivatives of the observables. The current work presents a method for eliminating such anti-causal components of the observables and lifting the system using only causal observables. The method is applied to excavation automation, a complex nonlinear dynamical system, to obtain a low-order lifted linear model for control design.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{Gieselmann2021,
title = {Planning-Augmented Hierarchical Reinforcement Learning},
author = {Robert Gieselmann and Florian T Pokorny},
doi = {10.1109/LRA.2021.3071062},
year = {2021},
date = {2021-01-01},
journal = {IEEE Robotics and Automation Letters},
volume = {6},
number = {3},
pages = {5097-5104},
abstract = {Abstract—Planning algorithms are powerful at solving longhorizon decision-making problems but require that environment dynamics are known. Model-free reinforcement learning has recently been merged with graph-based planning to increase the robustness of trained policies in state-space navigation problems. Recent ideas suggest to use planning in order to provide intermediate waypoints guiding the policy in long-horizon tasks. Yet, it is not always practical to describe a problem in the setting of state-to-state navigation. Often, the goal is defined by one or multiple disjoint sets of valid states or implicitly using an abstract task description. Building upon previous efforts, we introduce a novel algorithm called Planning-Augmented Hierarchical Reinforcement Learning (PAHRL) which translates the concept of hybrid planning/RL to such problems with implicitly defined goal. Using a hierarchical framework, we divide the original task, formulated as a Markov Decision Process (MDP), into a hierarchy of shorter horizon MDPs. Actor-critic agents are trained in parallel for each level of the hierarchy. During testing, a planner then determines useful subgoals on a state graph constructed at the bottom level of the hierarchy. The effectiveness of our approach is demonstrated for a set of continuous control problems in simulation including robot arm reaching tasks and the manipulation of a deformable object.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{styrud2021combining,
title = {Combining Planning and Learning of Behavior Trees for Robotic Assembly},
author = {Jonathan Styrud and Matteo Iovino and Mikael Norrlöf and Mårten Björkman and Christian Smith},
url = {https://arxiv.org/abs/2103.09036
https://arxiv.org/pdf/2103.09036
https://github.com/jstyrud/planning-and-learning
},
year = {2021},
date = {2021-01-01},
journal = {arXiv preprint arXiv:2103.09036},
abstract = {Industrial robots can solve very complex tasks in controlled environments, but modern applications require robots able to operate in unpredictable surroundings as well. An increasingly popular reactive policy architecture in robotics is Behavior Trees but as with other architectures, programming time still drives cost and limits flexibility. There are two main branches of algorithms to generate policies automatically, automated planning and machine learning, both with their own drawbacks. We propose a method for generating Behavior Trees using a Genetic Programming algorithm and combining the two branches by taking the result of an automated planner and inserting it into the population. Experimental results confirm that the proposed method of combining planning and learning performs well on a variety of robotic assembly problems and outperforms both of the base methods used separately. We also show that this type of high level learning of Behavior Trees can be transferred to a real system without further training.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{Li2020,
title = {Development of a vision-based target exploration system for snake-like robots in structured environments},
author = {Guoyuan Li and Håkon Bjerkgaard Waldum and Marcus Olai Grindvik and Ruben Svedal Jørundl and Houxiang Zhang},
url = {https://journals.sagepub.com/doi/full/10.1177/1729881420936141
https://www.researchgate.net/publication/342710008_Development_of_a_vision-based_target_exploration_system_for_snake-like_robots_in_structured_environments},
doi = {10.1177/1729881420936141},
year = {2020},
date = {2020-07-06},
journal = {International Journal of Advanced Robotic Systems},
pages = {1-11},
abstract = {Applying snake-like robots to environmental exploration has been a hot topic for years. How to achieve free navigation for target search in a complex environment in a safe and efficient manner is one of the main tasks that researchers in the field of robotics currently face. This article presents a target exploration system that takes advantages of visual sensing to navigate the snake-like robot in structured environments. Two cameras are utilized in the system. The first one is mounted on the head of the snake-like robot for target recognition and the other is an overhead camera which is responsible for locating the robot and identifying surrounding obstacles. All dead ends in the environment can thus be recognized using a template-based method. A search strategy for traversal of the dead ends is employed for generating exploration paths. Several gaits are developed for the snake-like robot. By switching between these gaits, the snake-like robot is able to follow the paths to search for the target. Two experiments are conducted in a maze environment. The experimental results validate the effectiveness of the proposed system for snake-like robots exploring in structured environments.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{major2020virtual,
title = {Virtual prototyping of offshore operations: a review},
author = {Pierre Major and Houxiang Zhang and Hans Petter Hildre and Mathieu Edet},
doi = {10.1080/09377255.2020.1831840},
year = {2020},
date = {2020-01-01},
journal = {Ship Technology Research},
pages = {1--18},
publisher = {Taylor & Francis},
abstract = {Virtual prototyping of offshore operations (VPOO) is performed to plan and validate planning of infrequent or demanding operations characterized by high risk and low margins of error in hostile and remote environments distant from emergency response bases that require expensive equipment. Key elements of VPOO is the rapidity of virtual prototyping and the human-centric approach necessitating high quality visuals and real-time time-domain simulation. This survey reviews publications, commercial software and simulators, and regulations on offshore operations. Findings indicate that the VPOO is not common in the industry, offshore operation regulations lag behind the state of the art in industry in terms of mission planning, and this field has been subject to scarce commercial and scientific scrutiny so far. A discussion of future developments and trends concludes the paper.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{yuan2020flexible,
title = {Flexible riser replacement operation based on advanced virtual prototyping},
author = {Shuai Yuan and Pierre Major and Houxiang Zhang},
doi = {10.1016/j.oceaneng.2020.107502},
year = {2020},
date = {2020-01-01},
journal = {Ocean Engineering},
volume = {210},
pages = {107502},
publisher = {Elsevier},
abstract = {As a critical campaign in the offshore oil and gas engineering, flexible riser replacements involve complex operations that need to be optimized and detailed to factor in trends in the industry. Since it allows engineers to interact with simulation tools in real time during the operation design phase, virtual prototyping (VP) is an efficient method to obtain an optimal solution and improve operational procedures in terms of safety and effectiveness for risk-based integrity management of flexible risers. In this study, a real-time VP model is adopted to simulate the process of a water injection flexible riser pulled in from an installation vessel to a jacket platform, which is one of the riser replacements tasks. The results are validated against results based on a finite element analysis. Attention is paid to the configuration, tension, and maximum bending curvature along the flexible riser during the operation. The innovative approach presented in this paper can provide guidance with respect to the operation limitations of a flexible pipe in practical engineering.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{yang2020time,
title = {Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator},
author = {Yajue Yang and Jia Pan and Pinxin Long and Xibin Song and Liangjun Zhang},
url = {https://arxiv.org/abs/2006.00811
https://arxiv.org/pdf/2006.00811},
year = {2020},
date = {2020-01-01},
journal = {arXiv preprint arXiv:2006.00811},
abstract = {In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates the excavation motion generation as a trajectory optimization problem and takes into account geometric, kinematic and dynamics constraints. To generate time-efficient trajectory and improve the overall optimization efficiency, we propose a time variable trajectory optimization mechanism so that the time intervals between the keypoints along the trajectory subject to the optimization. As a result, the method uses few keypoints and reduces the total number of optimization variables. We further introduce a soil-tool interaction force model, which considers the geometric shape of the bucket and the physical properties of the soil. The experimental result on a high fidelity dynamic simulator shows our method can generate feasible trajectories, which satisfy excavation task constraints and are adaptive to different soil conditions.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{wang2019visual,
title = {A visual simulation of ocean floating wind power system},
author = {Lin Wang and Hyuncheol Kim and Imgyu Kim and Soonhung Han},
doi = {10.1002/cav.1859},
year = {2019},
date = {2019-01-01},
journal = {Computer Animation and Virtual Worlds},
volume = {30},
number = {2},
pages = {e1859},
publisher = {Wiley Online Library},
abstract = {The development of ocean floating wind power has been burgeoning in recent years because of its low cost and high efficiency. To facilitate effectiveness, 3D visualization using virtual reality and augmented reality technologies has been applied to many operating systems. However, most of the existing 3D motion visualizations are “pseudo” visualization, and there are a few realistic visualization systems that base the motion of ocean floating wind power on simulation and experiment results. Therefore, in this paper, we conducted research related to the design for a realistic motion visualization system based on numerical simulation data using a commercial game engine (Unity 3D). In our system, the six‐degree‐of‐freedom motion (Surge, Sway, Heave, Roll, Pitch, and Yaw) is simulated and visualized based on numerical analysis results of two hydrodynamics simulation softwares, which can illuminate the nuance between simulation results and experiment results and give us a “real‐time” visual experience about motion in each direction. Meanwhile, comprehensive sea environment conditions, such as wind, rain, water, sound, and cloudiness, are also visualized in Unity 3D.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{major2019virtual,
title = {Virtual prototyping: a case study of positioning systems for drilling operations in the Barents Sea},
author = {Pierre Major and Robert Skulstad and Guoyuan Li and Houxiang Zhang},
doi = {10.1080/17445302.2019.1601322},
year = {2019},
date = {2019-01-01},
journal = {Ships and Offshore Structures},
volume = {14},
number = {sup1},
pages = {364--373},
publisher = {Taylor & Francis},
abstract = {This study proposes a framework for comparative study on three different positioning solutions for mobile offshore drilling units (MODUs) using high modulus polyethylene (HMPE) ropes, including active mooring with an HMPE rope, conventional dynamic positioning (DP) and active hybrid position-keeping (AHP-K). The goal of the positioning systems is to keep the MODU above the wellhead with acceptable riser-angle loading, minimal energy consumption, reduced underwater noise generation, and harmful emissions. This is the first time a holistic study has been performed on positioning that factors in the financial and environmental costs. The time domain simulation, which includes sea-state, wind, and current profiles, is performed with a well-developed software architecture and control algorithms for MODU position-keeping. The case study addresses a MODU drilling in the Barents Sea. Simulation results show that AHP-K is more efficient compared to the other two positioning solutions for drilling operations in the studied environment.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}

@article{park2016application,
title = {Application and validation of production planning simulation in shipbuilding},
author = {Kwang-Phil Park and Seung-Ho Ham and Chan-Young Lee},
doi = {10.1016/j.oceaneng.2016.01.008},
year = {2016},
date = {2016-01-01},
journal = {Ocean Engineering},
volume = {114},
pages = {154--167},
publisher = {Elsevier},
abstract = {As the weight and size of assembly blocks are getting increased, new production procedures by using floating cranes have been proposed to enhance the efficiency in shipyards. In this situation, simulation technology is required to evaluate potential risks of the procedure in advance. By such a necessity, we have developed a simulation system, named SIMSON (SIMulation System Of New production planning). SIMSON calculates the motion of the lifted block and floating bodies such as vessels and floating cranes based on the multibody system dynamics with the hydrostatic and hydrodynamic forces. The calculated motion and wire rope tension are used for dynamic effect estimation. In this paper, we present the application cases of SIMSON to real production process. The simulation results are compared by observing the situation in the real operations. The observation illustrates the simulation results are in harmony with the real situation and the application of SIMSON to production planning simulation in shipyards is quite feasible.},
keywords = {External},
pubstate = {published},
tppubtype = {article}
}