Tracking Sharks With Robots

Scientists have tracked sharks using robots for decades. But a new design allows them to do this while following the animal. The system was developed by biologists from Mote Marine Laboratory, and engineers from Harvey Mudd College using components that were readily available.

It is a formidable gripping device that can withstand pull-off forces of 340 times its own weight. It is also able to detect and adjust its pathway based on changing objects in the home.

Autonomous Underwater Vehicles (AUVs)

Autonomous underwater vehicle (AUV) are robots that are programmable and dependent on the design they can drift or move through the ocean, without any human supervision in real-time. They are equipped with a variety of sensors to monitor water parameters and explore and map the ocean’s geological features, sea floor habitats and communities and much more.

They are usually controlled from a surface vessel using Wi-Fi or an audio link to transmit data back to the operator. AUVS are utilized to collect any kind of temporal or spatial samples and are able to be deployed in large teams to cover more ground than is possible using one vehicle.

Like their land counterparts, AUVs can navigate using GPS and the Global Navigation Satellite System (GNSS) to determine where they are in the world and how far they’ve been from where they started. This positioning information, along with sensors for the environment that transmit information to the onboard computers, allows AUVs to follow a pre-planned course without losing sight of their destination.

When a research mission is complete, the AUV will float to the surface and then be returned to the research vessel from which it was launched. A resident AUV could remain underwater for months and conduct regular inspections that are pre-programmed. In either case, an AUV will periodically surface to communicate its position via a GPS or acoustic signal which is then transmitted to the surface vessel.

Some AUVs can communicate with their operators constantly through a satellite connection on the research vessel. This lets scientists continue to conduct experiments from their ship even when the AUV is collecting data under water. Other AUVs can communicate with their operators only at specific dates, like when they have to refill their tanks or to monitor the health of their sensors.

In addition to providing oceanographic information, AUVs can also be used to locate underwater resources, such as natural gas and minerals according to Free Think. They can also be employed in response to environmental disasters, such as tsunamis or oil spills. They can also be used to monitor volcanic activity in subsurface areas and monitor the condition of marine life, including whale populations and coral reefs.

Curious Robots

Contrary to conventional underwater robotics, which are preprogrammed to only search for one feature on the ocean floor, these curious underwater robots are designed so they can explore and adapt to changing circumstances. This is important because the environment beneath the waves can be unpredictable. If the water suddenly starts to heat up this could alter the behavior of marine animals or even result in an oil spill. The robots are designed to quickly and effectively detect changes in the environment.

One team of researchers is developing an innovative robotic platform that uses reinforcement learning to teach a robot to be curious about its surroundings. The robot, which resembles an infant wearing yellow clothing with a green hand, can be taught to recognize patterns, which could be a sign of an interesting discovery. It is also able to decide what it should do next, in relation to the results of its previous actions. The findings of the study could be used to design an intelligent robot that can learn and adapting itself to changing environments.

Scientists are also using robots to explore parts that are too dangerous for humans to dive into. Woods Hole Oceanographic Institution’s (WHOI), for example has a robot known as WARP-AUV which is used to search for shipwrecks and find them. This robot is able identify reef creatures and even discern fish and semi-transparent jellyfish from their dim backgrounds.

It takes years to train an individual to do this. The WARP-AUV’s brain is trained by feeding it thousands of images of marine life making it able to detect familiar species on its first dive. The WARP-AUV is a marine detective that also sends live images of sea creatures and underwater scenery to supervisors on the surface.

Other teams are working on robots that learn by observing the same curiosity humans have. A team at the University of Washington’s Paul G. Allen school of Computer Science & Engineering, for instance, is examining how to teach robots curiosity about their surroundings. The team is part of an Honda Research Institute USA initiative to create curious machines.

Remote Missions

There are many uncertainties that could lead to an unplanned mission failure. Scientists aren’t sure what time the mission will take, how well the components of the spacecraft will function or if other objects or forces will disrupt the spacecraft’s operations. The Remote Agent software is designed to eliminate these uncertainties. It will be able to perform a variety of the difficult tasks ground control personnel would perform if they were on DS1 at the time of the mission.

Remote Agent is a Remote Agent software system includes a planner/scheduler, executive model-based reasoning algorithm, and a. The planner/scheduler creates a set of time-based and event-based activities known as tokens which are then delivered to the executive. The executive decides how to use the tokens in a series of commands that are sent directly to spacecraft.

During the experiment during the test, a DS1 crewmember is on hand to assist in resolving any problems that may arise outside of the scope of the test. All regional bureaus must adhere to Department records management requirements and maintain all documents that is used to establish the remote mission.

SharkCam by Remus

Researchers aren’t aware of the activities of sharks below the surface. Scientists are piercing the blue veil with an autonomous underwater vehicle called the REMUS SharkCam. The results are astonishing and terrifying.

The SharkCam team is a group of Woods Hole Oceanographic Institution, took the torpedo-shaped SharkCam to Guadalupe Island last year to monitor and film great white sharks in their natural habitat. The 13 hours of video footage combined with the images from the acoustic tag that is attached to the sharks tell us a lot about their behavior underwater.

The REMUS sharkCam is manufactured by Hydroid in Pocasset MA, is designed to monitor the location of tag without affecting their behavior or causing alarm. It utilizes an Omnidirectional ultra-short baseline navigation system to determine the range, bearing and depth of the shark cordless vacuum self empty, then it closes in at a predetermined distance and location (left, right above or below) to film it swimming and interacting with its surroundings. It communicates with scientists on the surface every 20 seconds and can respond to commands to alter its speed and depth or standoff distance.

When state shark scientist Greg Skomal, WHOI engineer Amy Kukulya, Pelagios-Kakunja shark Stick vacuum self empty researcher Edgar Mauricio Hoyos-Padilla of Mexico’s Marine Conservation Society and REMUS SharkCam software developer Roger Stokey first envisioned tracking and filming great whites using the self-propelled torpedo that they named REMUS SharkCam, they worried that it could disturb the sharks’ movements and potentially scare them away from the area they were studying. However, in a recent article published in the Journal of Fish Biology, Skomal and his colleagues write that despite nine bites and bumps from great whites weighing thousands of pounds over the course of a week of research off the coast of Guadalupe the SharkCam survived–and revealed some intriguing new behaviors of the great white shark robotic vacuum cleaner.

Researchers interpreted the interactions between sharks and REMUS SharkCam (which was able to track four sharks tagged) as predatory behavior. They recorded 30 shark interactions with the robot including simple approaches, bumps and on nine occasions, aggressive bites by sharks that appeared to be targeting REMUS.