Difference between revisions of "Smart sensor"
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− | |Summary= | + | |Summary=Small smart sensors |
− | |Keywords= | + | |Keywords=Smart sensors, adaptation, sensors |
|TimeFrame=First half of 2018 | |TimeFrame=First half of 2018 | ||
− | |References= | + | |References=Surya G. Nurzaman, Utku Culha, Luzius Brodbeck, Liyu Wang, Fumiya Iida. (2013) Active Sensing System with In Situ Adjustable Sensor Morphology. PLoS ONE 8(12):e84090. doi:10.1371/journal.pone.0084090 |
− | + | Robin R. Murphy. Dempster–Shafer Theory for Sensor Fusion in Autonomous Mobile Robots. IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, VOL. 14, NO. 2, APRIL 1998 197. | |
− | |Prerequisites= | + | |Prerequisites=Projects involving both software, hardware, and electronics require much development/time |
− | |Supervisor=Martin | + | |Supervisor=Martin Cooney (possibly Håkan Petterson) |
|Level=Master | |Level=Master | ||
|Status=Open | |Status=Open | ||
}} | }} | ||
− | + | Goal: small smart sensors | |
− | + | Motivation: | |
− | + | Current sensors are "static", detecting just one thing, such as light, sound, or touch, because of which in complex systems such as vehicles or homes many sensors are typically required. | |
− | + | A "smart" sensor which could dynamically adapt itself (to detect different signals) could replace multiple static sensors, leading to less space taken, less cost, less work for installations, a greater ability to operate when changes occur, and possibly even easier repairs (self-healing). | |
− | + | Alternatively, an ensemble of dynamic sensors could acquire more information than the same number of static sensors. | |
− | + | Furthermore, if such sensors can be made small, various benefits would emerge: e.g., making arbitrary surfaces embedded with sensors for robots such as intelligent skin, and interesting tasks at the micro scale could potentially be facilitated, such as monitoring cells inside of a person. | |
− | + | Challenges: | |
− | + | It is unknown how a sensor could be automatically changed into a different kind of sensor, a good strategy for changing a sensor or an ensemble of sensors, and how to achieve this at a small scale. | |
− | + | Approach: | |
+ | The student will | ||
+ | -Design transitions between some typical sensors | ||
+ | -Design algorithms for calculating information/interestingness for each modality (possibly using change point detection) and for strategically allocating roles (like particles in a particle filter). | ||
+ | -Design a strategy for the micro scale | ||
+ | -Implement a macro-scale proof-of-concept, which can be switched manually or algorithmically, and a smaller proof-of-concept (mini, or micro; nano would be cool but would probably not be possible) | ||
+ | -Evaluate | ||
+ | -Thus, students will develop both software, and hardware/electronics | ||
+ | Expected result: some ideas (new knowledge) of how to adapt different sensors, at different scales. Thesis, prototypes, video, hopefully a paper, possibly other such as code |
Revision as of 17:10, 23 November 2017
Title | Smart sensor |
---|---|
Summary | Small smart sensors |
Keywords | Smart sensors, adaptation, sensors |
TimeFrame | First half of 2018 |
References | Surya G. Nurzaman, Utku Culha, Luzius Brodbeck, Liyu Wang, Fumiya Iida. (2013) Active Sensing System with In Situ Adjustable Sensor Morphology. PLoS ONE 8(12):e84090. doi:10.1371/journal.pone.0084090
Robin R. Murphy. Dempster–Shafer Theory for Sensor Fusion in Autonomous Mobile Robots. IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, VOL. 14, NO. 2, APRIL 1998 197. |
Prerequisites | Projects involving both software, hardware, and electronics require much development/time |
Author | |
Supervisor | Martin Cooney (possibly Håkan Petterson) |
Level | Master |
Status | Open |
Goal: small smart sensors
Motivation:
Current sensors are "static", detecting just one thing, such as light, sound, or touch, because of which in complex systems such as vehicles or homes many sensors are typically required.
A "smart" sensor which could dynamically adapt itself (to detect different signals) could replace multiple static sensors, leading to less space taken, less cost, less work for installations, a greater ability to operate when changes occur, and possibly even easier repairs (self-healing).
Alternatively, an ensemble of dynamic sensors could acquire more information than the same number of static sensors.
Furthermore, if such sensors can be made small, various benefits would emerge: e.g., making arbitrary surfaces embedded with sensors for robots such as intelligent skin, and interesting tasks at the micro scale could potentially be facilitated, such as monitoring cells inside of a person.
Challenges:
It is unknown how a sensor could be automatically changed into a different kind of sensor, a good strategy for changing a sensor or an ensemble of sensors, and how to achieve this at a small scale.
Approach:
The student will
-Design transitions between some typical sensors
-Design algorithms for calculating information/interestingness for each modality (possibly using change point detection) and for strategically allocating roles (like particles in a particle filter).
-Design a strategy for the micro scale
-Implement a macro-scale proof-of-concept, which can be switched manually or algorithmically, and a smaller proof-of-concept (mini, or micro; nano would be cool but would probably not be possible)
-Evaluate
-Thus, students will develop both software, and hardware/electronics
Expected result: some ideas (new knowledge) of how to adapt different sensors, at different scales. Thesis, prototypes, video, hopefully a paper, possibly other such as code