{"id":330,"date":"2024-11-21T00:36:27","date_gmt":"2024-11-21T00:36:27","guid":{"rendered":"https:\/\/blogs.oregonstate.edu\/marineautonomy\/?page_id=330"},"modified":"2024-12-05T19:48:06","modified_gmt":"2024-12-05T19:48:06","slug":"autonomous-subsea-robotic-manipulation","status":"publish","type":"page","link":"https:\/\/blogs.oregonstate.edu\/marineautonomy\/autonomous-subsea-robotic-manipulation\/","title":{"rendered":"Autonomous Subsea Robotic Manipulation"},"content":{"rendered":"\n

Sponsor: Office of Naval Research
ONR Award Number: N00024-10-D-6318 \/ DO#N0002420F8705
Project Leads: Aaron Marburg (UW), Joe Davidson (OSU), Geoff Hollinger (OSU)
Project Dates: April 2020-April 2024<\/p>\n\n\n\n

This project conducted fundamental research in control, perception, planning, and human interfaces to enable dexterous, robust, and flexible robotic manipulation in underwater environments.<\/p>\n\n\n\n

The project’s motivation is the development of semi-autonomous remotely operated vehicles (ROVs) capable of performing complex tasks such as hull cleaning or environmental sampling, in highly energetic conditions. An operator would provide high-level commands to the vehicle through an interface that provides advanced decision support, and the commands would be interpreted and executed using advanced robotic perception and trajectory optimization and control algorithms. The vehicle would use a soft gripper attached to a high-degree-of-freedom arm with onboard touch sensing to feel its way around the environment and provide a robust grasp.<\/p>\n\n\n\n

The project developed technologies in test environments, beginning with operation and manipulation of robotic arms on fixed, underwater test stands. The project\u2019s four thrust areas included (1) perception and object identification, (2) gripper and tactile sensing, (3) decision support, and (4) trajectory optimization.<\/p>\n\n\n\n

Link to short videos<\/a> to learn more about this project\u2019s components.<\/p>\n\n\n

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The project developed an underWater Arm Vehicle Emulator (WAVE) to support testing of motion control and sensing in hydrodynamic environments. (Image credit: Aaron Marburg, UW APL)<\/figcaption><\/figure>\n<\/div>\n\n\n

Publications & Presentations<\/h2>\n\n\n\n

2024<\/h3>\n\n\n\n

S.  Chow, Learning-based Techniques for Fast and Robust Motion Planning<\/a>, PhD Thesis, Oregon State University, Corvallis, OR, March, 2024.<\/p>\n\n\n\n

Yixuan Huang, Jialin Yuan, Chanho Kim, Pupul Pradhan, Bryan Chen, Li Fuxin, Tucker Hermans.  Out of Sight, Still in Mind: Reasoning and Planning about Unobserved Objects with Video Tracking Enabled Memory Models<\/a>.  In Proc.  IEEE International Conference on Robotics and Automation<\/em> (ICRA), Yokohama, Japan, 2024. <\/p>\n\n\n\n

M. Jiang, S Khorram, F.Li.\u00a0Comparing the Decision-Making Among Transformers and CNNs with Explanation Methods<\/a>. IEEE\/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, 2024. Best Student Paper Runner-Up.<\/p>\n\n\n\n

M.\u00a0 Rosette, H.\u00a0 Kolano, C.\u00a0 Holm, G.A.\u00a0 Hollinger, A.\u00a0 Marburg, M.\u00a0 Pickett, and J.R.\u00a0 Davidson, \u201cWAVE: An open-source underWater Arm-Vehicle Emulator<\/a>,\u201d Accepted to the IEEE International Conference on Robotics and Automation<\/em>, Yokohama, Japan, May 2024.<\/p>\n\n\n\n

A. Ullah, T. Yan, F. Li.\u00a0 CVAE-SM: A Conditional Variational Autoencoder with Style Modulation for Efficient Uncertainty Quantification.\u00a0 In Proc.\u00a0 IEEE International Conference on Robotics and Automation <\/em>(ICRA), 2024.\u00a0<\/p>\n\n\n\n

2023<\/h3>\n\n\n\n

S.\u00a0 Bhawsinghka, N.\u00a0 Troxler, S.\u00a0 Walker, and J.R.\u00a0 Davidson, \u201cHydraulic modulation of silicone knuckles for variable control of joint stiffness,\u201d In Proceedings of the<\/em> 6th IEEE-RAS International Conference on Soft Robotics (RoboSoft 2023)<\/em>, Singapore, Apr.\u00a0 2023, 6pp.\u00a0<\/p>\n\n\n\n

S.\u00a0 Chow, D.\u00a0 Chang, and G.\u00a0 Hollinger, “Parallelized control-aware motion planning with learned controller proxies<\/a>,” Robotics and Automation Letters<\/em>, vol.\u00a0 8, no.\u00a0 4.\u00a0 pp.\u00a0 2237-2244, April 2023.\u00a0<\/p>\n\n\n\n

M. Jiang, S. Khorram, Li, F.\u00a0 \u201cDiverse Explanations for Object Detectors with Nesterov-Accelerated iGOS++\u00a0<\/a>\u201c,\u201d\u00a0 in Proc.\u00a0 British Machine Vision Conference (BMVC), Aberdeen, UK, 2023.\u00a0<\/p>\n\n\n\n

Wesley Khademi, Li Fuxin.\u00a0 Diverse Shape Completion via Style-Modulated Generative Adversarial Networks.\u00a0 In Proc.\u00a0 Neural Information Processing Systems<\/em> (NeuRIPS), New Orleans, LA, USA, 2023.<\/p>\n\n\n\n

W. Khademi, F. Li.  \u201cDiverse Shape Completion via Style-Modulated Generative Adversarial Networks<\/a>,\u201d  In Proc.  Neural Information Processing Systems (NeuRIPS), New Orleans, LA, USA, 2023. <\/p>\n\n\n\n

H.  Kolano and J.R.  Davidson, \u201cForecasting vehicle pitch and roll of a lightweight UVMS with recurrent neural networks,\u201d In Proceedings of the IEEE\/RSJ Int\u2019l Conf.  on Intelligent Robots and Systems (IROS) Workshop on: Robotics for the Blue Economy and Climate Resiliency, Detroit, MI<\/a>, Oct.  2023, 1pp. <\/p>\n\n\n\n

T.\u00a0 Player, D.\u00a0 Chang, L.\u00a0 Fuxin, and G.\u00a0 Hollinger, “Real-time generative grasping with spatio-temporal sparse convolution<\/a>,” in Proceedings of the IEEE International Conference on Robotics and Automation<\/em>, London, UK, May 2023.\u00a0<\/p>\n\n\n\n

N.  Pusalkar, M.-R.  Giolando, and J.  A.  Adams, \u201cDecision Support System for Autonomous Underwater Robot Grasping<\/a>,\u201d Late Breaking Report, Proceedings of the Companion of ACM\/IEEE International Conference on Human-Robot Interaction, <\/em>pp 198-202, 2023. <\/p>\n\n\n\n

N.  Pusalkar, M.-R.  Gioland, and J.  A.  Adams, \u201cAutonomous Underwater Robot Grasping Decision Support System<\/a>,\u201d Abstract and Video, Proceedings of the Companion of ACM\/IEEE International Conference on Human-Robot Interaction, <\/em>pp 887-888, 2023.  <\/p>\n\n\n\n

2022<\/h3>\n\n\n\n

A.  Agrawal, D.  Chang, and G.  Hollinger, “Task and motion planning for collective robotic construction<\/a>,” in Proc.  IEEE International Conference on Robotics and Automation Workshop on Collective Robotic Construction<\/em> (ICRA), Philadelphia, PA, May 2022.<\/p>\n\n\n\n

M.\u00a0 Pickett, H.\u00a0 Kolano, J.R.\u00a0 Davidson, and A.\u00a0 Marburg, \u201cDesign of a robotic testbed for underwater manipulation research,\u201d In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA): Workshop on Robotics for Climate Change<\/em>, Philadelphia, PA, May 2022, 3pp.\u00a0<\/p>\n\n\n\n

K.\u00a0 Puente, S.\u00a0 Walker, J.\u00a0 Davidson, and G.\u00a0 Hollinger, \u201cDesign and grasp planning for a reconfigurable variable stiffness underwater robotic hand<\/a>,\u201d in Proc.\u00a0 IEEE International Conference on Robotics and Automation Workshop on Compliant Manipulation<\/em> (ICRA), Philadelphia, PA, May 2022.\u00a0<\/p>\n\n\n\n

K.  Sullivan, H.  Chizeck, A.  Marburg \u201cUsing a rigid gripper on objects of difference compliances underwater<\/a>.\u201d  in MTS\/IEEE Oceans Conference 2022, Hampton Roads.  <\/em>October 2022. <\/p>\n\n\n\n

B.  Stoddard, M.  Cravetz, T.  Player, H.  Knight \u201cA Haptic Multimodal Interface with Abstract Controls for Semi-Autonomous Manipulation<\/a>.\u201c HRI Video Demo in Proceedings of the International Conference on Human-Robot Interaction (HRI 2022), Virtual Event.  March 2022. <\/p>\n\n\n\n

2021<\/h3>\n\n\n\n

D.  Chang, S.  Chow, T.  R.  Player, and G.  A.  Hollinger, \u201cAdaptive and informative planning for an underwater vehicle-manipulator system<\/a>,\u201d Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) Workshop on Advanced Marine Robotics: Active Perception<\/em>, 2021.<\/p>\n\n\n\n

S.  Chow, G.  Olson, and G.  Hollinger, “Compensating for unmodeled forces using neural networks in soft manipulator planning<\/a>,” in Proc.  IEEE International Conference on Robotics and Automation<\/em> (ICRA), Xi’ian, China, May 2021. <\/p>\n\n\n\n

\u00a0L.\u00a0 Lindzey and A.\u00a0 Marburg, “Extrinsic Calibration between an Optical Camera and an Imaging Sonar<\/a>,” OCEANS 2021<\/em>: San Diego \u2013 Porto, 2021, pp.\u00a0 1-8.\u00a0<\/p>\n\n\n\n

M.\u00a0 Scott and A.\u00a0 Marburg, “Quantifying the Degradation of Optical Algorithms in Increasingly Turbid Mediums<\/a>,” OCEANS 2021<\/em>: San Diego \u2013 Porto, 2021, pp.\u00a0 1-10.\u00a0<\/p>\n\n\n\n

Return to projects page<\/a>…<\/p>\n","protected":false},"excerpt":{"rendered":"

Sponsor: Office of Naval ResearchONR Award Number: N00024-10-D-6318 \/ DO#N0002420F8705Project Leads: Aaron Marburg (UW), Joe Davidson (OSU), Geoff Hollinger (OSU)Project Dates: April 2020-April 2024 This project conducted fundamental research in control, perception, planning, and human interfaces to enable dexterous, robust, and flexible robotic manipulation in underwater environments. The project’s motivation is the development of semi-autonomous … <\/p>\n

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