Ocean exploration is the foundation for marine wildlife and climate change research.

Current ocean exploration methods have major trade-offs in speed and adaptability. Working solutions by WHOI have major logistic and technological problems that inhibit efficient and adaptive ocean exploration.

RAPID is an Autonomous Underwater Vehicle (AUV) designed to quickly gather in-situ ocean data and actively swarm around areas of interest that it may detect.

Designed At MIT, course 2.013: Engineering Systems Design.
All rights reserved.

The team:

Austin Anthis, Christina Meyer, Jairo Rodriguez Tovar, Jeevesh Konuru, Jo Pierre, Lance Neil, Max Beeman, Max Raven, Miana Smith, Ryan Flores, Samer Awale, and Tianqi Zheng.


Expensive to deploy

  • Most AUVs are big robots that need large transportation vessels to be deployed. Each mission involves several people. It has an impact on mission cost (renting the vessels and its crewman) and timing (mission planning/logistics).

Adaptability for diversity

  • Current AUVs have specific set of capabilities, some work for some specific mission and some others for other set of missions limiting missions scope and adding cost on operations and taking longer mission time..

Turnaround time matters

  • There are critical missions that require quick turnaround. The ability to make informed decisions and react to difficult circumstances is priceless and can safe entire ecosystems.


Vertical Speed drifts ~0.02m/s ~0.25m/s 1m/s
Horizontal Speed none none none 0.25m/s
Converge on Areas of Interest no no no yes
Data Return Time 2 years 10 days 4 hrs 1 hr
Data Collection  salinity (CTD) position salinity (CTD) position salinity (CTD) position salinity (CTD)     position modular 
Weight 10 kg 40 kg  10 kg 41 kg
Operating Depth 0-2500m 1000m-2000m 1000m 1000 m



35 years old

Environmental scientist and marine ecologist who teaches and does research at Oregon State University. Her research interests include interactions between the environment and human well-being, biodiversity, climate change, and sustainable use of oceans and the planet.

46 years old

Scientist who has worked in the fields of geology, oceanography, and the origins of life. Corliss is a University of California, San Diego Alumnus, receiving his PhD from Scripps Institution of Oceanography

28 years old

Works on oceanographic missions. Some of the task he does are: lift 25-50 lbs independently, 1-5 times per day; carry 10-25 lbs, 1-5 times per day. He has to have good vision including  peripheral, depth perception, and ability to distinguish basic colors. As well as good gearing, include the ability to hear and respond to instructions, communicate effectively in loud areas (pier/dock, warehouse).


System Requirements RAPID
Vertical Ascent/Descent Speed 1m/s
Horizontal Lateral Speed  0.25 m/s
Converge on Areas of Interest Yes
Data Return Time 1 hour
Data Collection Types salinity (CTD), position, modular
Weight < 46 kg
Operating Depth 1000 m

RAPID is designed to handle a multitude of sensors with its modular sensor interface. The system is design to scale accordingly with the mission needs.  It has the capability to be deployed in vast numbers in order to collect as much volumetric data as possible. To support this, the system has been designed to be simple and robust.

System UI


RAPID is an AUV that utilizes a piston-based buoyancy engine to vertically descend and ascend up to 1000m into the ocean. Each AUV is equipped with two actively controlled fins in order to laterally move along the ocean. Using these fins and an on-board communication suite of acoustic and satellite signals, multiple RAPID AUVs can swarm to areas of interest and a volume of data. While each RAPID AUV can measure water temperature, depth, and salinity.

Robotic System

RAPID is designed to acquire, process, and transmit data autonomously. For an end user, the process of deploying RAPID involves uploading a file with customized mission information, physically deploying the swarm near the region(s) of interest, receiving live updates of interesting data, collecting all of the vehicles, and offloading all of the collected data.

Each AUV is able to navigate and acquire data autonomously. By looking for significant changes in the data it collects, RAPID can determine locations of interest. By communicating with each other, AUVs are able to cluster around locations of interest, which allows for more efficient collection of data and the ability to track temporally changing effects.


In addition, each AUV also periodically transmits interesting information back to the research base, so that the end-user can receive almost live updates from the AUVs.  A high-level illustration of the use process is shown in the figure below. The end user should be able to pick a region of interest on a map, deploy the AUVs, and get back an efficiently sampled version of that map. 

Two Vehicle Swarm

Step 1

Step 2

Step 3

Step 4


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