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Sim2Real in Robotics and Automation: Applications and Challenges

Sebastian Hofer, Kostas Bekris, Ankur Handa, Juan Camilo Gamboa, Melissa Mozifian, Florian Golemo, Chris Atkeson, Dieter Fox, Ken Goldberg, John Leonard, C. Karen Liu, Jan Peters (+3 others)
2021 IEEE Transactions on Automation Science and Engineering  
Sim2Real in Robotics and Automation: Applications and Challenges T O PERFORM reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation.  ...  This editorial highlights opportunities and challenges related to Sim2Real in automation.  ... 
doi:10.1109/tase.2021.3064065 fatcat:3poitbdvwfc6xlwweewpz5b4lu

The Importance and the Limitations of Sim2Real for Robotic Manipulation in Precision Agriculture [article]

Carlo Rizzardo, Sunny Katyara, Miguel Fernandes, Fei Chen
2020 arXiv   pre-print
In recent years Sim2Real approaches have brought great results to robotics.  ...  An example is agricultural robotics, which needs detailed simulations, both in terms of dynamics and visuals. However, simulation software is still not capable of such quality and accuracy.  ...  Sim2Real Setup for Grapevine Pruning In our implementation a robot composed of a wheeled mobile platform and a robot arm has to navigate in the vineyard, locate the vines, identify spurs and pruning locations  ... 
arXiv:2008.03983v1 fatcat:v7oaid7mfvhtvjsq6gqwynoogq

A Metaverse: taxonomy, components, applications, and open challenges

Sang-Min Park, Young-Gab Kim
2022 IEEE Access  
, implementation, and application) rather than marketing or hardware approach to conduct a comprehensive analysis.  ...  Finally, we summarize the limitations and directions for implementing the immersive Metaverse as social influences, constraints, and open challenges.  ...  They use Real2sim for bridging the visual domain gap and sim2real for linking the dynamic domain gap. 7) DISCUSSION AND OPEN CHALLENGES As mentioned above, Facebook research is a research group with  ... 
doi:10.1109/access.2021.3140175 fatcat:fnraeaz74vh33knfvhzrynesli

2020 Index IEEE Robotics and Automation Letters Vol. 5

2020 IEEE Robotics and Automation Letters  
., +, LRA April 2020 774-781 Addressing the Sim2Real Gap in Robotic 3-D Object Classification.  ...  ., +, LRA April 2020 2602-2609 Trajectory Optimization for Wheeled-Legged Quadrupedal Robots Driving in Challenging Terrain.  ... 
doi:10.1109/lra.2020.3032821 fatcat:qrnouccm7jb47ipq6w3erf3cja

RoboCup 2021 Worldwide: A Successful Robotics Competition During a Pandemic [Competitions]

Peter Stone, Luca Iocchi, Flavio Tonidandel, Changjiu Zhou
2021 IEEE robotics & automation magazine  
Acknowledgments The authors would like to thank the more than 2,000 participants in RoboCup 2021, who are the lifeblood of our community.  ...  We especially thank all the members of the OC (https://2021.robocup .org/organization), the RoboCup trustees, the executive committee members, the league TC members, and the OC members of the leagues.  ...  One very salient challenge that was particularly apparent this year is the problem known as Sim2Real: enabling robot behaviors to be learned in simulation, with comparatively abundant computation and data  ... 
doi:10.1109/mra.2021.3117413 fatcat:zp6jlkvfwfcavfpcqq6ithy74i

2021 Index IEEE Robotics and Automation Letters Vol. 6

2021 IEEE Robotics and Automation Letters  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  ., +, LRA Oct. 2021 6939-6946 Machine Learning in Manufacturing Ergonomics: Recent Advances, Challenges, and Opportunities.  ... 
doi:10.1109/lra.2021.3119726 fatcat:lsnerdofvveqhlv7xx7gati2xu

2021 Index IEEE Transactions on Automation Science and Engineering Vol. 18

2021 IEEE Transactions on Automation Science and Engineering  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  Xiao, Q., +, TASE April 2021 717-730 Sim2Real in Robotics and Automation: Applications and Challenges.  ... 
doi:10.1109/tase.2021.3120615 fatcat:ybfn4kfdvjfipbty7z3mocjjci

Table of Contents

2021 IEEE Robotics and Automation Letters  
Kyriakopoulos 2005 In Defense of Knowledge Distillation for Task Incremental Learning and Its Application in 3D Object Detection .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Pan, and L. Zhang 1479 Self-Organised Saliency Detection and Representation in Robot Swarms . . . . . .M. Alhafnawi, S. Hauert, and P.  ... 
doi:10.1109/lra.2021.3072707 fatcat:qyphyzqxfrgg7dxdol4qamrdqu

Sim2real gap is non-monotonic with robot complexity for morphology-in-the-loop flapping wing design [article]

Kent Rosser, Jia Kok, Javaan Chahl, Josh Bongard
2019 arXiv   pre-print
identified and further optimised in a future end-to-end automated morphology design process.  ...  We developed a parameterised morphology design space that draws features from biological exemplars and apply automated design to produce a set of high performance robot morphologies in simulation.  ...  Automated design of these robots in simulation is challenged by the "reality gap" problem [14] .  ... 
arXiv:1910.13790v1 fatcat:pdwkhyh2qfchfcm7xtsebcu3h4

Unified Automatic Control of Vehicular Systems With Reinforcement Learning

Zhongxia Yan, Abdul Rahman Kreidieh, Eugene Vinitsky, Alexandre M. Bayen, Cathy Wu
2022 IEEE Transactions on Automation Science and Engineering  
This is a key challenge to efficient analysis of diverse vehicular and mobility systems.  ...  Emerging vehicular systems with increasing proportions of automated components present opportunities for optimal control to mitigate congestion and increase efficiency.  ...  Moreover, we argue that near-future Sim2Real extensions of our work are feasible for fully automated robotic systems, which may require movement and coordination of automated vehicular robots with assigned  ... 
doi:10.1109/tase.2022.3168621 fatcat:ueyw32q5preuxmzo2iys3sy7tu

"What's This?" - Learning to Segment Unknown Objects from Manipulation Sequences

Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel
2021 2021 IEEE International Conference on Robotics and Automation (ICRA)  
In contrast to previous approaches, we propose a single, end-toend trainable architecture which jointly incorporates motion cues and semantic knowledge.  ...  Furthermore, while the motion of the manipulator and the object are substantial cues for our algorithm, we present means to robustly deal with distraction objects moving in the background, as well as with  ...  annotated segmentation masks, and we additionally label the respective robot arms for a complete evaluation of foreground, robot and object.  ... 
doi:10.1109/icra48506.2021.9560806 fatcat:vpqg4gyuxbcb3dica4s5nnqf5y

Model-Based Manipulation of Linear Flexible Objects: Task Automation in Simulation and Real World

Peng Chang, Taşkın Padır
2020 Machines  
We demonstrate the feasibility of our approach by completing the Plug Task used in the 2015 DARPA Robotics Challenge Finals both in simulation and real world, which involves unplugging a power cable from  ...  These models enable task automation in manipulating linear flexible objects both in simulation and real world.  ...  The DARPA Robotics Challenge (DRC) Simulator (DRCSim) and the Space Robotics Challenge Simulation (SRCSim) have related open-source simulations for most tasks in the competition.  ... 
doi:10.3390/machines8030046 fatcat:gsnrdj43kzennloneyx2dnavrq

Learning Deformable Object Manipulation from Expert Demonstrations

Gautam Salhotra, I-Chun Arthur Liu, Marcus Dominguez-Kuhne, Gaurav S. Sukhatme
2022 IEEE Robotics and Automation Letters  
We deploy DMfD on a real robot with a minimal loss in normalized performance during real-world execution compared to simulation (~6%). Source code is on  ...  Additionally, we create two challenging environments for folding a 2D cloth using image-based observations, and set a performance benchmark for them.  ...  BACKGROUND Deformable object manipulation has been a challenge in robotics with many real-world applications, such as folding clothes [6] , cooking food [7] , or assisting humans [8] .  ... 
doi:10.1109/lra.2022.3187843 fatcat:ts2ml2gis5ffhewjsgu3vx6gqa

Study on Data-Driven Approaches for the Automated Assembly of Board-to-Board Connectors

Hsien-I Lin, Fauzy Satrio Wibowo, Ashutosh Kumar Singh
2022 Applied Sciences  
Thus, it is essential to automate the assembly process to ensure its safety and reliability during the mating process.  ...  In the experiment, the proposed RP-CNN model used two final layers, SoftMax and L2-SVM, to compare with the other prediction models mentioned above.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Data sharing not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12031216 fatcat:g4vabd2u7bfm7lziiz6eaj2tbq

Analysis of Randomization Effects on Sim2Real Transfer in Reinforcement Learning for Robotic Manipulation Tasks [article]

Josip Josifovski, Mohammadhossein Malmir, Noah Klarmann, Bare Luka Žagar, Nicolás Navarro-Guerrero, Alois Knoll
2022 arXiv   pre-print
Randomization is currently a widely used approach in Sim2Real transfer for data-driven learning algorithms in robotics.  ...  We compare four randomization strategies with three randomized parameters both in simulation and on a real robot.  ...  Three commonly used parameters in Sim2Real transfer in robotics were randomized: Latency, Torque, and Sensor and Motor noise.  ... 
arXiv:2206.06282v1 fatcat:uaua24e2qjhqxex63zj5yxyy64
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