Design Summary and Analysis Draft 1

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 According to the article “Soft robotic arm uses flexible sensors to understand its position” (Matheson, 2020), researchers from Massachusetts Institute of Technology (MIT) have developed a system comprising of sensors with high compliance and an information processing model which allows a robot equipped with these to know it’s position in 3D space efficiently. Traditionally, robots get their configuration info from a complex system of cameras, which are unfeasible for actual soft robots applications. “We’re sensorizing soft robots to get feedback for control from sensors, not vision systems, using a very easy, rapid method for fabrication.” said Ryan Truby. The entire system is still inadequate, but it is a crucial foothold from which advances in soft robotic control can be made. Moving ahead, researchers are looking at designing better sensors and learning models to cut down on training for new robots.


Matheson (2020) Soft robotic arm uses flexible sensors to understand its position https://www.controleng.com/articles/soft-robotic-arm-uses-flexible-sensors-to-understand-its-position/nd its position

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summary and analysis Draft 1

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According to the article “Soft robotic arm...” (Matheson, 2020), researchers from the Massachusetts Institute of Technology (MIT) have developed a system comprising of sensors with high compliance and an information processing model that allows a robot equipped with these to know it’s position in 3D space efficiently. The sensors are wrapped all around the robot’s body like skin. Traditionally, robots get their configuration info from a complex system of cameras, which are unfeasible for actual soft robot applications. Ryan Truby, one of the researchers, said that “We’re sensorizing soft robots to get feedback for control from sensors, not vision systems, using a very easy, rapid method for fabrication.”. He also said that the entire system is still inadequate, but it is a crucial foothold from which advances in soft robotic control can be made. Moving ahead, researchers are looking at designing better sensors and learning models to cut down on training for new robots. Although the sof
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  Summary and Analysis Draft #4   MEC1281   Woravuth Chong (2003006)   According to the article “Soft robotic arm...” (Matheson, 2020), researchers from the Massachusetts Institute of Technology (MIT) have developed a system comprising of sensors with high compliance and an information processing model that allows a robot equipped with these to know its position in 3D space and move about efficiently. The sensors are wrapped all around the robot’s body like skin. Traditionally, robots get their configuration info from a complex system of cameras, which are unfeasible for actual soft robot applications. Truby, one of the researchers, said that “We’re sensorising soft robots to get feedback for control from sensors, not vision systems, using a very easy, rapid method for fabrication.” According to Matheson, Truby also said that the entire system is still inadequate, but it is a crucial foothold from which advances in soft robotic control can be made. Moving ahead, researchers
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