東華大學圖書館 |

Miniaturized Robotics and Wireless for Environmental Sensing.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Miniaturized Robotics and Wireless for Environmental Sensing./
作者:	Elkunchwar, Nishant Girish.
面頁冊數:	1 online resource (62 pages)
附註:	Source: Masters Abstracts International, Volume: 83-08.
Contained By:	Masters Abstracts International83-08.
標題:	Robotics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28775112click for full text (PQDT)
ISBN:	9798780636045

Miniaturized Robotics and Wireless for Environmental Sensing.
Elkunchwar, Nishant Girish.

Miniaturized Robotics and Wireless for Environmental Sensing. - 1 online resource (62 pages)

Source: Masters Abstracts International, Volume: 83-08.

Thesis (Master's)--University of Washington, 2021.

Includes bibliographical references

Commercially available sub-gram (20-30 mg), low cost sensors can enable sensing for a wide variety of applications. Recently developed insect scale robots like the University of Washington Robofly make for an ideal candidate to make use of these sub-gram sensors. Moreover, these sensors can also be attached to birds or insects to study their behaviors, like foraging patterns, body temperature etc. However, a number of challenges need to be addressed before such systems can be deployed on insects or robots at this scale. This thesis focuses on solutions to three particular problems in this area: implementation and demonstration of a biology-inspired source seeking algorithm, persistent operation of aerial robots by harvesting solar power, and development of a sensing platform for insect behavior studies. The results show that miniaturizing hardware and designing robot behavior inspired from biology can help solve these challenges. As advances in this domain lead to stable flight with aerial insect scale robots, the results shown in this work can help deploy teams of such robots to search for any number of hazardous sources over a long period of time without the need to set up a power infrastructure. This can be particularly useful in disaster-struck areas. Not only does this work show solution to these problems by implementing biology-inspired algorithms and enabling persistent operation, but it also develops a platform that can help study the behavior of other species, leading to more biology-driven robot development.Chapter 1 - The small form factor of palm sized unmanned aerial vehicles (UAVs) combined with their ability to freely maneuver in 3D space with holonomic trajectories and carry custom sensors makes them an ideal platform for autonomous source seeking in challenging environments. Equipped with the appropriate sensor, a small UAV could autonomously navigate towards light or heat sources such as forest fires or locate a radio-frequency (RF) transmitter attached to anything from a package in a warehouse to an animal tagged with a radio tracker. Leveraging small UAVs for this task however requires addressing their size weight, power, and computational constraints. While prior source seeking robots have used search strategies that require extensive training, such as reinforcement learning, we instead look to biology and employ a simple 'run and tumble' gradient following algorithm inspired by bacterial chemotaxis. The result is a computationally inexpensive approach requiring as little as 30 instructions/second, allowing this strategy to scale down to millimeter scale robots with small microcontrollers. Using insights from simulation, we report a success rate of 91% in real-time demonstrations of our UAV navigating towards a fire or light source while avoiding obstacles. Measurements from a small Bluetooth transmitter indicate it also produces a compatible gradient at ranges of 50-100 m. We conclude by discussing how this technique could scale down to sub-cm microrobots seeking RF power sources.Chapter 2 - Constrained battery life on current Unmanned Aerial Vehicles (drones) limits the time they can operate and distance they can travel. We address this challenge by harvesting solar power to enable duty-cycled operation on a palm-sized drone. We present a scaling analysis that suggests that more solar power can be collected per unit mass of the drone as scale reduces, favoring small drones. By charging from the sun, the drone can operate for more than a single charging cycle, enabling extended mission time, and long-distance travel. To realize this, we design a high efficiency charging circuit and introduce two innovations. The first is a photovoltaic array that passively folds down while in flight to reduce air drag and automatically opens during landing due to the ground effect. The second is a sensor system and controller that autonomously finds suitable charging sites that are flat and well-lit. The drone can be fully charged in 3 hrs using the solar array and charging circuit with an average efficiency of 90.84%. Each charge enables a 4.7 min flight, allowing the drone to travel up to 1.2 km in a day. We also discuss how this platform could be used to take periodic measurements for smart agriculture or wildlife tracking, rapidly deploy wireless networks, or deploy microrobots in the future.Chapter 3 - Lightweight sensors coupled with wireless chips can help understand insect behavior. We first program an existing bluetooth enabled platform attached to an invasive Asian hornet species, Vespa mandarinia, to transmit sensor measurements to nearby receivers and also store them on-board. We demonstrate the utility of the system by tagging a live hornet and collecting data from it. We also design and fabricate another platform with a VHF radio and a microcontroller. This platform makes it easier to integrate new components and test application programs while still weighing just 113 mg and can be used for a wide variety of environmental sensing applications.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798780636045Subjects--Topical Terms:

519753
Robotics.
Subjects--Index Terms:

Biology inspiredIndex Terms--Genre/Form:

542853
Electronic books.

Miniaturized Robotics and Wireless for Environmental Sensing.
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As advances in this domain lead to stable flight with aerial insect scale robots, the results shown in this work can help deploy teams of such robots to search for any number of hazardous sources over a long period of time without the need to set up a power infrastructure. This can be particularly useful in disaster-struck areas. Not only does this work show solution to these problems by implementing biology-inspired algorithms and enabling persistent operation, but it also develops a platform that can help study the behavior of other species, leading to more biology-driven robot development.Chapter 1 - The small form factor of palm sized unmanned aerial vehicles (UAVs) combined with their ability to freely maneuver in 3D space with holonomic trajectories and carry custom sensors makes them an ideal platform for autonomous source seeking in challenging environments. Equipped with the appropriate sensor, a small UAV could autonomously navigate towards light or heat sources such as forest fires or locate a radio-frequency (RF) transmitter attached to anything from a package in a warehouse to an animal tagged with a radio tracker. Leveraging small UAVs for this task however requires addressing their size weight, power, and computational constraints. While prior source seeking robots have used search strategies that require extensive training, such as reinforcement learning, we instead look to biology and employ a simple 'run and tumble' gradient following algorithm inspired by bacterial chemotaxis. The result is a computationally inexpensive approach requiring as little as 30 instructions/second, allowing this strategy to scale down to millimeter scale robots with small microcontrollers. Using insights from simulation, we report a success rate of 91% in real-time demonstrations of our UAV navigating towards a fire or light source while avoiding obstacles. Measurements from a small Bluetooth transmitter indicate it also produces a compatible gradient at ranges of 50-100 m. We conclude by discussing how this technique could scale down to sub-cm microrobots seeking RF power sources.Chapter 2 - Constrained battery life on current Unmanned Aerial Vehicles (drones) limits the time they can operate and distance they can travel. We address this challenge by harvesting solar power to enable duty-cycled operation on a palm-sized drone. We present a scaling analysis that suggests that more solar power can be collected per unit mass of the drone as scale reduces, favoring small drones. By charging from the sun, the drone can operate for more than a single charging cycle, enabling extended mission time, and long-distance travel. To realize this, we design a high efficiency charging circuit and introduce two innovations. The first is a photovoltaic array that passively folds down while in flight to reduce air drag and automatically opens during landing due to the ground effect. The second is a sensor system and controller that autonomously finds suitable charging sites that are flat and well-lit. The drone can be fully charged in 3 hrs using the solar array and charging circuit with an average efficiency of 90.84%. Each charge enables a 4.7 min flight, allowing the drone to travel up to 1.2 km in a day. We also discuss how this platform could be used to take periodic measurements for smart agriculture or wildlife tracking, rapidly deploy wireless networks, or deploy microrobots in the future.Chapter 3 - Lightweight sensors coupled with wireless chips can help understand insect behavior. We first program an existing bluetooth enabled platform attached to an invasive Asian hornet species, Vespa mandarinia, to transmit sensor measurements to nearby receivers and also store them on-board. We demonstrate the utility of the system by tagging a live hornet and collecting data from it. We also design and fabricate another platform with a VHF radio and a microcontroller. This platform makes it easier to integrate new components and test application programs while still weighing just 113 mg and can be used for a wide variety of environmental sensing applications.
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650 4 $a Remote sensing. $3 535394
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653 $a Drone recharging
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653 $a Miniaturized wireless environmental sensing
653 $a Solar charging
653 $a Source seeking
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773 0 $t Masters Abstracts International $g 83-08.
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