{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/155889"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/155889","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Proximity Sensors for a High-Bandwidth, Low-Latency Robotic Manipulation Object Avoidance Controller","abstract":"Robotics holds the promise of transforming industries, from automating recycling to managing household chores, by enabling machines to perform tasks with human-like dexterity. However, current robotic manipulation systems struggle to achieve the real-time responsiveness required for such tasks. Traditional systems rely on cameras, which slow down control loops with dense and difficult-to-process data. This thesis addresses the need for real-time control in robotic manipulation by utilizing proximity sensors in a high-bandwidth, low-latency object avoidance reflex controller on the Biomimetic Robotics Lab’s dexterous robotic manipulation platform. The research focuses on the two most viable proximity sensors for robotic manipulation: the STMicroelectronics VL6180X Time-of-Flight sensor and the Thinker Phase-Modulated-Light sensor. These sensors are characterized based on their measurement range, error, variance, field-of-view, and convergence time to determine their usability in an object avoidance reflex. Following characterization, a study on the integration of these sensors into the manipulation platform is performed to assess sensing latency and bandwidth implications. Finally, validation of the optimal sensor-controller configuration for the object avoidance reflex—averaging two time-of-flight sensors with a linear virtual force—shows an improvement in bandwidth from 33 Hz to 115 Hz, enhancing the reactivity and stability of the object avoidance reflex. Overall, this research provides a comprehensive study on the individual sensor and sensor-integration levels of proximity sensors for object avoidance reflexes. It enables future researchers to be confident in the manipulation platform’s performance for further controls-level research.","abstract_html":"Robotics holds the promise of transforming industries, from automating recycling to managing household chores, by enabling machines to perform tasks with human-like dexterity. However, current robotic manipulation systems struggle to achieve the real-time responsiveness required for such tasks. Traditional systems rely on cameras, which slow down control loops with dense and difficult-to-process data. This thesis addresses the need for real-time control in robotic manipulation by utilizing proximity sensors in a high-bandwidth, low-latency object avoidance reflex controller on the Biomimetic Robotics Lab’s dexterous robotic manipulation platform. The research focuses on the two most viable proximity sensors for robotic manipulation: the STMicroelectronics VL6180X Time-of-Flight sensor and the Thinker Phase-Modulated-Light sensor. These sensors are characterized based on their measurement range, error, variance, field-of-view, and convergence time to determine their usability in an object avoidance reflex. Following characterization, a study on the integration of these sensors into the manipulation platform is performed to assess sensing latency and bandwidth implications. Finally, validation of the optimal sensor-controller configuration for the object avoidance reflex—averaging two time-of-flight sensors with a linear virtual force—shows an improvement in bandwidth from 33 Hz to 115 Hz, enhancing the reactivity and stability of the object avoidance reflex. Overall, this research provides a comprehensive study on the individual sensor and sensor-integration levels of proximity sensors for object avoidance reflexes. It enables future researchers to be confident in the manipulation platform’s performance for further controls-level research.","abstract_has_math":false,"creators":["Han, Jessica"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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However, current robotic manipulation systems struggle to achieve the real-time responsiveness required for such tasks. Traditional systems rely on cameras, which slow down control loops with dense and difficult-to-process data. This thesis addresses the need for real-time control in robotic manipulation by utilizing proximity sensors in a high-bandwidth, low-latency object avoidance reflex controller on the Biomimetic Robotics Lab’s dexterous robotic manipulation platform. The research focuses on the two most viable proximity sensors for robotic manipulation: the STMicroelectronics VL6180X Time-of-Flight sensor and the Thinker Phase-Modulated-Light sensor. These sensors are characterized based on their measurement range, error, variance, field-of-view, and convergence time to determine their usability in an object avoidance reflex. Following characterization, a study on the integration of these sensors into the manipulation platform is performed to assess sensing latency and bandwidth implications. Finally, validation of the optimal sensor-controller configuration for the object avoidance reflex—averaging two time-of-flight sensors with a linear virtual force—shows an improvement in bandwidth from 33 Hz to 115 Hz, enhancing the reactivity and stability of the object avoidance reflex. Overall, this research provides a comprehensive study on the individual sensor and sensor-integration levels of proximity sensors for object avoidance reflexes. It enables future researchers to be confident in the manipulation platform’s performance for further controls-level research."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Proximity Sensors for a High-Bandwidth, Low-Latency Robotic Manipulation Object Avoidance Controller"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kim, Sangbae"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Mechanical Engineering"],"dc:creator":["Han, Jessica"],"dc:date.accessioned":["2024-08-01T19:04:01Z"],"dc:date.available":["2024-08-01T19:04:01Z"],"dc:date.issued":["2024-05"],"dc:description.abstract":["Robotics holds the promise of transforming industries, from automating recycling to managing household chores, by enabling machines to perform tasks with human-like dexterity. However, current robotic manipulation systems struggle to achieve the real-time responsiveness required for such tasks. Traditional systems rely on cameras, which slow down control loops with dense and difficult-to-process data. This thesis addresses the need for real-time control in robotic manipulation by utilizing proximity sensors in a high-bandwidth, low-latency object avoidance reflex controller on the Biomimetic Robotics Lab’s dexterous robotic manipulation platform. The research focuses on the two most viable proximity sensors for robotic manipulation: the STMicroelectronics VL6180X Time-of-Flight sensor and the Thinker Phase-Modulated-Light sensor. These sensors are characterized based on their measurement range, error, variance, field-of-view, and convergence time to determine their usability in an object avoidance reflex. Following characterization, a study on the integration of these sensors into the manipulation platform is performed to assess sensing latency and bandwidth implications. Finally, validation of the optimal sensor-controller configuration for the object avoidance reflex—averaging two time-of-flight sensors with a linear virtual force—shows an improvement in bandwidth from 33 Hz to 115 Hz, enhancing the reactivity and stability of the object avoidance reflex. Overall, this research provides a comprehensive study on the individual sensor and sensor-integration levels of proximity sensors for object avoidance reflexes. It enables future researchers to be confident in the manipulation platform’s performance for further controls-level research."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/155889"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Proximity Sensors for a High-Bandwidth, Low-Latency Robotic Manipulation Object Avoidance Controller"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Mechanical Engineering"]},"updated_at":"2026-07-22T22:22:03Z"}