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Tracking Sharks With Robots
Scientists have been tracking sharks using robots for a long time, but a new design is able to do this while following the animal. The system was designed by biologists from Mote Marine Laboratory, and engineers from Harvey Mudd College using components that were readily available.
It can withstand a pull-off force 400 times greater than its own weight. It can also sense and adjust its pathway based on changing objects in the home.
Autonomous Underwater Vehicles
Autonomous underwater vehicles (AUV) are robots that can be programmed to operate dependent on the design they can drift or move through the ocean, without human-controlled control in real-time. They are equipped with a variety of sensors that record water parameters and explore and map the ocean's geological features, seafloor habitats and communities, and more.
They are controlled by a surface ship by using Wi-Fi or acoustic links to send data back to the operator. AUVS are able to collect spatial or temporal data and can be used as a group to cover more ground quicker than a single vehicle.
AUVs are able to use GPS and a Global Navigation Satellite System to determine where they are around the globe and the distance they've traveled from their initial location. This positioning information, along with sensors in the environment that transmit data to the computer systems onboard, allows AUVs to travel on a planned trajectory without losing track of their goals.
After completing a research mission after completing a research project, the AUV will be able to float back to the surface. It can be then recovered by the research vessel from which it was launched. A resident AUV may also remain underwater for months and perform regular inspections pre-programmed. In either case, the AUV will periodically surface to signal its location using an GPS signal or acoustic beacon, which are then transmitted to the surface ship.
Certain AUVs communicate with their operator continuously through satellite links on the research vessel. This lets scientists continue conducting experiments from the ship even when the AUV is away collecting data underwater. Other AUVs can communicate with their operators only at certain dates, like when they have to refill their tanks or verify the status of their sensor systems.
In addition to providing oceanographic data, AUVs can also be used to locate underwater resources such as minerals and natural gas, according to Free Think. They can also be used as part of an environmental disaster response plan to aid in search and rescue operations following oil spills or tsunamis. They can be used to monitor subsurface volcano activity and also the conditions of marine life, such as whale populations or coral reefs.
Curious Robots
Contrary to conventional underwater robotics, which have been programmed to search for one feature on the ocean floor, the curious underwater robots are designed they can explore and adapt to changing circumstances. This is important, because the conditions below the waves can be unpredictable. For instance, if the water suddenly gets warmer, it could change the behavior of marine creatures or cause an oil spill. Robots that are curious can detect the changes swiftly and efficiently.
One team of researchers is developing a new robotic shark platform that uses reinforcement learning to train a robot to be curious about its surroundings. The robot, which looks like a child, complete with yellow jacket and a green arm can be taught to detect patterns that could suggest an interesting discovery. It is also able to make decisions based on its past actions. The results of this research could be used to develop an intelligent robot that is capable of learning and adapting itself to changing environments.
Researchers are also using robots to explore areas that are dangerous for humans to dive. Woods Hole Oceanographic Institution's (WHOI), for example has a robot known as WARP-AUV that is used to study wrecks of ships and to locate them. This robot is able to recognize reef creatures and discern jellyfish and semi-transparent fish from their dim backgrounds.
This is a remarkable feat considering the time it takes to train a human to do this work. The brain of the WARP-AUV has been trained to recognize familiar species after thousands of images have been fed into it. In addition to its abilities as a marine sleuth, the WARP-AUV has the ability to send topside supervisors real-time pictures of underwater scenery and sea creatures.
Other teams are developing robots that learn by observing the same curiosity humans have. 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 part of a Honda Research Institute USA initiative to develop curious machines.
Remote Missions
There are a lot of uncertainties in space missions that can lead to mission failure. Scientists don't know for sure how long a mission will last, how well the spacecraft parts will function, or if any other forces or objects might interfere with spacecraft operation. The Remote Agent software is designed to reduce these uncertainties. It will perform many of the complicated tasks ground control personnel would do if they were DS1 at the time of the mission.
The Remote Agent software system includes a planner/scheduler, an executive, and model-based reasoning algorithms. The planner/scheduler generates a set of time-based, event-based activities known as tokens which are sent to the executive. The executive decides how to use the tokens in an array of commands that are sent directly to spacecraft.
During the experiment during the test, an DS1 crew member will be present to keep track of the progress of the Remote Agent and deal with any issues that are not within the scope of the test. All regional bureaus must follow Department records management guidelines and maintain all documentation pertaining to the establishment of a remote mission.
SharkCam by REUS
Researchers aren't aware of the activities of sharks beneath the surface. Scientists are cutting through the blue barrier by using an autonomous underwater vehicle named the REMUS SharkCam. The results are both incredible and terrifying.
The SharkCam team, a group from Woods Hole Oceanographic Institution, took the torpedo-shaped SharkCam to Guadalupe Island last year to observe and film great white sharks in their natural habitat. The 13 hours of video footage combined with the visuals from the acoustic tag attached to the sharks reveal much about their behavior underwater.
The REMUS SharkCam, developed in Pocasset, MA by Hydroid, is designed to follow the location of an animal that has been tagged without disturbing its behavior or alarming it. It is a ultra-short navigation system to determine the range, bearing and depth of the animal. Then it closes in on the shark with a predetermined distance and position (left or right above or below) and records its swimming and interaction with its surroundings. It can communicate with scientists on the surface every 20 seconds and respond to commands to alter relative speed and depth, as well as the standoff distance.
When state shark scientist Greg Skomal, WHOI engineer Amy Kukulya, Pelagios-Kakunja shark self-emptying robot vacuum researcher Edgar Mauricio Hoyos-Padilla from Mexico's Marine Conservation Society and REMUS SharkCam software creator Roger Stokey first envisioned tracking and filming great whites with the self emptying robot vacuum shark-propelled torpedo they called REMUS SharkCam, they worried that it would disturb the sharks' movements and could scare them away from the area they were studying. Skomal and his colleagues, wrote in a recent paper published in the Journal of Fish Biology that the SharkCam survived despite nine bumps and a biting attack from great whites weighing several thousand pounds over a week of research along the coast of Guadalupe.
The researchers concluded that the sharks interactions with REMUS SharkCam, a robot that was recording and tracking the activity of four sharks that were tagged, as predatory behavior. Researchers recorded 30 shark detect pro self-empty robot vacuum interactions, including simple bumps and nine bites that were aggressive.
Scientists have been tracking sharks using robots for a long time, but a new design is able to do this while following the animal. The system was designed by biologists from Mote Marine Laboratory, and engineers from Harvey Mudd College using components that were readily available.
It can withstand a pull-off force 400 times greater than its own weight. It can also sense and adjust its pathway based on changing objects in the home.
Autonomous Underwater Vehicles
Autonomous underwater vehicles (AUV) are robots that can be programmed to operate dependent on the design they can drift or move through the ocean, without human-controlled control in real-time. They are equipped with a variety of sensors that record water parameters and explore and map the ocean's geological features, seafloor habitats and communities, and more.
They are controlled by a surface ship by using Wi-Fi or acoustic links to send data back to the operator. AUVS are able to collect spatial or temporal data and can be used as a group to cover more ground quicker than a single vehicle.
AUVs are able to use GPS and a Global Navigation Satellite System to determine where they are around the globe and the distance they've traveled from their initial location. This positioning information, along with sensors in the environment that transmit data to the computer systems onboard, allows AUVs to travel on a planned trajectory without losing track of their goals.
After completing a research mission after completing a research project, the AUV will be able to float back to the surface. It can be then recovered by the research vessel from which it was launched. A resident AUV may also remain underwater for months and perform regular inspections pre-programmed. In either case, the AUV will periodically surface to signal its location using an GPS signal or acoustic beacon, which are then transmitted to the surface ship.
Certain AUVs communicate with their operator continuously through satellite links on the research vessel. This lets scientists continue conducting experiments from the ship even when the AUV is away collecting data underwater. Other AUVs can communicate with their operators only at certain dates, like when they have to refill their tanks or verify the status of their sensor systems.
In addition to providing oceanographic data, AUVs can also be used to locate underwater resources such as minerals and natural gas, according to Free Think. They can also be used as part of an environmental disaster response plan to aid in search and rescue operations following oil spills or tsunamis. They can be used to monitor subsurface volcano activity and also the conditions of marine life, such as whale populations or coral reefs.
Curious Robots
Contrary to conventional underwater robotics, which have been programmed to search for one feature on the ocean floor, the curious underwater robots are designed they can explore and adapt to changing circumstances. This is important, because the conditions below the waves can be unpredictable. For instance, if the water suddenly gets warmer, it could change the behavior of marine creatures or cause an oil spill. Robots that are curious can detect the changes swiftly and efficiently.
One team of researchers is developing a new robotic shark platform that uses reinforcement learning to train a robot to be curious about its surroundings. The robot, which looks like a child, complete with yellow jacket and a green arm can be taught to detect patterns that could suggest an interesting discovery. It is also able to make decisions based on its past actions. The results of this research could be used to develop an intelligent robot that is capable of learning and adapting itself to changing environments.
Researchers are also using robots to explore areas that are dangerous for humans to dive. Woods Hole Oceanographic Institution's (WHOI), for example has a robot known as WARP-AUV that is used to study wrecks of ships and to locate them. This robot is able to recognize reef creatures and discern jellyfish and semi-transparent fish from their dim backgrounds.
This is a remarkable feat considering the time it takes to train a human to do this work. The brain of the WARP-AUV has been trained to recognize familiar species after thousands of images have been fed into it. In addition to its abilities as a marine sleuth, the WARP-AUV has the ability to send topside supervisors real-time pictures of underwater scenery and sea creatures.
Other teams are developing robots that learn by observing the same curiosity humans have. 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 part of a Honda Research Institute USA initiative to develop curious machines.
Remote Missions
There are a lot of uncertainties in space missions that can lead to mission failure. Scientists don't know for sure how long a mission will last, how well the spacecraft parts will function, or if any other forces or objects might interfere with spacecraft operation. The Remote Agent software is designed to reduce these uncertainties. It will perform many of the complicated tasks ground control personnel would do if they were DS1 at the time of the mission.
The Remote Agent software system includes a planner/scheduler, an executive, and model-based reasoning algorithms. The planner/scheduler generates a set of time-based, event-based activities known as tokens which are sent to the executive. The executive decides how to use the tokens in an array of commands that are sent directly to spacecraft.
During the experiment during the test, an DS1 crew member will be present to keep track of the progress of the Remote Agent and deal with any issues that are not within the scope of the test. All regional bureaus must follow Department records management guidelines and maintain all documentation pertaining to the establishment of a remote mission.
SharkCam by REUS
Researchers aren't aware of the activities of sharks beneath the surface. Scientists are cutting through the blue barrier by using an autonomous underwater vehicle named the REMUS SharkCam. The results are both incredible and terrifying.
The SharkCam team, a group from Woods Hole Oceanographic Institution, took the torpedo-shaped SharkCam to Guadalupe Island last year to observe and film great white sharks in their natural habitat. The 13 hours of video footage combined with the visuals from the acoustic tag attached to the sharks reveal much about their behavior underwater.
The REMUS SharkCam, developed in Pocasset, MA by Hydroid, is designed to follow the location of an animal that has been tagged without disturbing its behavior or alarming it. It is a ultra-short navigation system to determine the range, bearing and depth of the animal. Then it closes in on the shark with a predetermined distance and position (left or right above or below) and records its swimming and interaction with its surroundings. It can communicate with scientists on the surface every 20 seconds and respond to commands to alter relative speed and depth, as well as the standoff distance.
When state shark scientist Greg Skomal, WHOI engineer Amy Kukulya, Pelagios-Kakunja shark self-emptying robot vacuum researcher Edgar Mauricio Hoyos-Padilla from Mexico's Marine Conservation Society and REMUS SharkCam software creator Roger Stokey first envisioned tracking and filming great whites with the self emptying robot vacuum shark-propelled torpedo they called REMUS SharkCam, they worried that it would disturb the sharks' movements and could scare them away from the area they were studying. Skomal and his colleagues, wrote in a recent paper published in the Journal of Fish Biology that the SharkCam survived despite nine bumps and a biting attack from great whites weighing several thousand pounds over a week of research along the coast of Guadalupe.
The researchers concluded that the sharks interactions with REMUS SharkCam, a robot that was recording and tracking the activity of four sharks that were tagged, as predatory behavior. Researchers recorded 30 shark detect pro self-empty robot vacuum interactions, including simple bumps and nine bites that were aggressive.
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