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Challenges and Opportunities for Underwater Robotics Dr. Yi Guo Department of Electrical and Computer Engineering Stevens Institute of Technology Email: [email protected] In Collaboration with Dr. Brian Bingham at University of Hawaii NSF Sponsored Workshop at AAAI Conference, Austin, Jan. 25, 2015
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Page 1: Challenges and Opportunities for Underwater Roboticsrobotics.cs.tamu.edu/nsfboundaryws/slides/Distributed_Guo_Austin_v... · Challenges and Opportunities for Underwater Robotics Dr.

Challenges and Opportunities for Underwater Robotics

Dr. Yi GuoDepartment of Electrical and Computer Engineering

Stevens Institute of TechnologyEmail: [email protected]

In Collaboration with Dr. Brian Bingham at University of Hawaii

NSF Sponsored Workshop at AAAI Conference, Austin, Jan. 25, 2015

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Challenge

• Recent deepwater horizon oil spill has posed great challenges to both robotics and ocean engineering communities

• It is challenging to estimate the extent of the underwater plume

• The challenges will continue to grow as energy production continues to happen in ever deeper water

Oil slick seen from NASA satellite. Source: Wikipedia

Page 3: Challenges and Opportunities for Underwater Roboticsrobotics.cs.tamu.edu/nsfboundaryws/slides/Distributed_Guo_Austin_v... · Challenges and Opportunities for Underwater Robotics Dr.

Opportunity• Utilizing advanced robotics

techniques to improve the capability of ocean robots in conducting autonomous cooperating tasks

• Filling the gap between new algorithmic approaches and field deployments that impact our ability to observe, explore and manage ocean resources

Contour plot of the selected ion monitoring detection from a mass spectrometer coupled with acoustic positioning. Pic. from Dr. B. Bingham at Univ. of Hawaii

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Overall Objectives

• The development of advanced multi-robot cooperative deployment algorithms for oceanographicalapplications;

• The development of authentic dynamic models of operational ocean robots to integrate in advanced cooperative control algorithms;

• The implementation and integration of advanced algorithms on heterogeneous ocean robots, and experimental demonstration of the efficacy in real-world coastal environments

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Algorithm Development

• Distributed dynamic plume tracking– Advection-diffusion equation to model oil

plume distribution

– Deploy multi-robots to dynamically track the plume front

– Nearest neighbor communication

• Challenges:– Incorporating plume dynamic model – Computational efficiency– Limited communication for multiple robots

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Matlab Simulation

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Towards Field Tests

• Challenges:– Environment and plume data– Transition between simulation and field tests– Sensing– Vehicle dynamics– Field deployment

Algorithm development Simulation validation

Simulation in Robot Simulator Controller laboratory test

Field tests

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The Plume Model

Page 9: Challenges and Opportunities for Underwater Roboticsrobotics.cs.tamu.edu/nsfboundaryws/slides/Distributed_Guo_Austin_v... · Challenges and Opportunities for Underwater Robotics Dr.

Simulation in Field Robotics Lab Vehicle Software (FVS) Platform

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Laboratory Experiment vs Field Test


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