Väitös (tietoteknologia): MSc Sherif Mohamed
Aika
17.2.2023 klo 12.15 - 16.15
MSc Sherif Mohamed esittää väitöskirjansa ”Runtime Resource Management for vision-based Applications in Mobile Robots” julkisesti tarkastettavaksi Turun yliopistossa perjantaina 17.2.2023 klo 12:15 (Turun yliopisto, Agora, LS XXI, Vesilinnantie 5, Turku).
Vastaväittäjänä toimii apulaisprofessori Amir Hossein Payberah (KTH Kuninkaallinen teknillinen korkeakoulu, Ruotsi) ja kustoksena professori Juha Plosila (Turun yliopisto). Tilaisuus on englanninkielinen. Väitöksen alana on tietoteknologia.
Väitöskirja yliopiston julkaisuarkistossa: https://urn.fi/URN:ISBN:978-951-29-9146-4 (kopioi linkki selaimeen).
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Tiivistelmä väitöstutkimuksesta:
This thesis investigates new approaches to improve performance and energy efficiency of computer vision (CV) applications in mobile robots. The goal is to balance accuracy, performance, and energy consumption in real-time. The authors adjust algorithmic and computational parameters and consider the robot's speed as an actuator in their resource management algorithm. Experiments were conducted on an unmanned ground vehicle powered by a Jetson TX2 board and equipped with RGB and event cameras. Results showed noticeable improvement in performance and accuracy while reducing energy consumption compared to state-of-the-art solutions. The authors also found that considering both computational and mechanical aspects together reduced energy consumption more than considering them separately.
Vastaväittäjänä toimii apulaisprofessori Amir Hossein Payberah (KTH Kuninkaallinen teknillinen korkeakoulu, Ruotsi) ja kustoksena professori Juha Plosila (Turun yliopisto). Tilaisuus on englanninkielinen. Väitöksen alana on tietoteknologia.
Väitöskirja yliopiston julkaisuarkistossa: https://urn.fi/URN:ISBN:978-951-29-9146-4 (kopioi linkki selaimeen).
***
Tiivistelmä väitöstutkimuksesta:
This thesis investigates new approaches to improve performance and energy efficiency of computer vision (CV) applications in mobile robots. The goal is to balance accuracy, performance, and energy consumption in real-time. The authors adjust algorithmic and computational parameters and consider the robot's speed as an actuator in their resource management algorithm. Experiments were conducted on an unmanned ground vehicle powered by a Jetson TX2 board and equipped with RGB and event cameras. Results showed noticeable improvement in performance and accuracy while reducing energy consumption compared to state-of-the-art solutions. The authors also found that considering both computational and mechanical aspects together reduced energy consumption more than considering them separately.