Tracking Sharks With Robots

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

It can resist a pull-off force of 340 times greater than its own weight. It also can detect changes in objects and alter its direction in line with the changes.

Autonomous Underwater Vehicles

Autonomous underwater vehicles (AUVs) are robots that are programmable and according to their design they can drift, move or glide across the ocean without real-time control from human operators. They are equipped with sensors that monitor water parameters, search and map features of the ocean's geology and habitats and more.

They are typically controlled from a surface vessel via Wi-Fi or an acoustic link to send data back to the operator. AUVS are able to collect spatial or temporal data, and are able to be used in a larger group to cover more ground more quickly than a single vehicle.

Similar to their counterparts on land, AUVs can navigate using GPS and a Global Efficient Navigation Shark Robot Vacuum With Alexa Satellite System (GNSS) to determine where they are in the world and how far they've been from where they started. This information, along with sensors for the environment that send information to the computer systems onboard, allows AUVs follow their intended course without losing sight of the goal.

After completing a research mission after completing a research project, the AUV will float up to the surface. It will be retrieved by the research vessel from where it was launched. A resident AUV could remain submerged for a long time and perform regular inspections pre-programmed. In either case the AUV will periodically surface to transmit its location via the GPS or acoustic signal, which is sent to the vessel that is on the surface.

Certain AUVs can communicate with their operators on a continuous basis via a satellite connection on the research vessel. This allows scientists to continue conducting experiments from the ship while the AUV is off collecting data underwater. Other AUVs can communicate with their operators only at specified times, such as when they need to refuel or check the status of their sensors.

Free Think says that AUVs are not only used to collect data from oceanography but also to search underwater resources, like minerals and gas. They can also be utilized to assist in environmental disaster response and aid in rescue and search operations following tsunamis or oil spills. They can also be used to monitor subsurface volcano activity and the conditions of marine life, including whale populations or coral reefs.

Curious Robots

In contrast to traditional underwater robots, which are preprogrammed to look for a single feature of the ocean floor The more curious robots are designed to look around and adapt to changing conditions. This is crucial because the underwater environment can be unpredictable. For instance, if the water suddenly gets warmer it could alter the behavior of marine animals or even cause an oil spill. Robots that are curious are designed to swiftly and effectively detect these changes.

Researchers are working on a new robotic platform that makes use of reinforcement learning to train robots to be curious. The robot, which appears like a child with yellow clothing and a green arm can be trained to spot patterns that could suggest an interesting discovery. It can also learn to make decisions about what it should do next, in relation to the results of its previous actions. The results of this research could be used to create an intelligent robot that is capable of learning and adapting to changing environments.

Researchers are also using robots to study areas that are too hazardous for humans to dive. Woods Hole Oceanographic Institute's (WHOI), for example, has a robot called WARP-AUV which is used to investigate wrecks of ships and to locate them. The robot can recognize reef creatures and discern jellyfish and semi-transparent fish from their dim backgrounds.

It takes a long time to learn to be able to do this. The brain of the WARP-AUV has been trained recognize familiar species after a lot of images have been fed into it. The WARP-AUV is a marine detective that can also send live images of sea creatures and underwater scenery to supervisors at the surface.

Other teams are working to create robots that share the same curiosity as humans. For instance, a team led by the University of Washington's Paul G. Allen School of Computer Science & Engineering is investigating ways to teach robots to be curious about their surroundings. This team is a part of an Honda Research Institute USA initiative to create curious machines.

Remote Missions

There are a lot of uncertainties in space missions that could cause mission failure. Scientists aren't sure how long the mission's events will take, how well certain parts of the spacecraft will work, or if other forces or objects could disrupt the spacecraft's operations. The Remote Agent software is designed to reduce these uncertainties. It will perform many of the difficult tasks that ground personnel would do if they were DS1 at the time of the mission.

The Remote Agent software system consists of a planner/scheduler and an executive. It also incorporates models-based reasoning algorithms. The planner/scheduler produces a set of activities based on time and events called tokens which are then sent to the executive. The executive determines how to expand the tokens into a series of commands which are sent directly to spacecraft.

During the experiment during the test, a DS1 crewmember will be available to keep track of the progress of the Remote Agent and deal with any problems outside the scope of the test. All regional bureaus should follow Department requirements for records management and maintain all documents used in conjunction with establishing a specific remote mission.

SharkCam by REMUS

Researchers aren't aware of the activities of sharks beneath the surface. But researchers using an autonomous underwater vehicle known as SharkCam from REMUS are beginning to break through the blue layer and the results are both astonishing and frightening.

The SharkCam Team, a group of scientists from Woods Hole Oceanographic Institution took the SharkCam the torpedo-shaped camera and to Guadalupe Island to track and film white great sharks in their natural habitat. The 13 hours of video footage with the images from the acoustic tag attached to the sharks reveal much about their underwater behavior.

The REMUS sharkCam is manufactured by Hydroid in Pocasset MA, is designed to follow the location of a tag without affecting their behavior or alarming them. It employs an omnidirectional ultra-short baseline navigation system to determine the range, bearing, and depth of the shark, then it closes in at a predetermined standoff distance and location (left or right above or below) to film it swimming and interacting with its surroundings. It can communicate with scientists at the surface every 20 seconds and can respond to commands to change speed and depth, as well as the standoff distance.

State shark scientist Greg Skomal, WHOI engineer Amy Kukulya, Pelagios-Kakunja Efficient Shark AI Robot Vacuum with Smart Mapping researcher Edgar Mauricio Hoyos-Padilla of Mexico's Marine Conservation Society and REMUS SharkCam software creator Roger Stokey first envisioned tracking and filming great whites using the self-propelled torpedo, which they named REMUS SharkCam they were worried that it could disturb the sharks' movements, and possibly cause them to flee from the area they were studying. In a recent article published in the Journal of Fish Biology, Skomal and his colleagues report that despite nine bites and bumps from great whites that weighed thousands of pounds during 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.

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