Computational modeling of insect-inspired visuomotor control applied to autonomous mobile systems
This DSTL-funded four year PhD project aims to translate biological principles of visual information processing into guidance and control architectures of autonomous robotic platforms. Insect-inspired mechanisms underlying visual attitude control and tracking will be integrated in a simulation framework to study the simultaneous performance of inner-loop stabilization tasks and outer-loop goal-directed behaviors. The project will be supervised/co-supervised by Prof Holger Krapp and Dr Huai-Ti Lin, respectively. The project may be tailored slightly to include some hardware integration but the main focus will be computational.
The long term goal of the project is to exploit the benefits of an active vision system (e.g. 3~6-axis camera gimbal) to improve the performance of low size, weight and power (SWAP) terrestrial and aerial platforms with different dynamics and under various environmental conditions. The results are relevant for general applications in autonomous platforms operating in GPS-denied scenarios, and allow for integration of other sensory inputs such as spectral, acoustic and chemical information.
The anticipated start date of this position is between 15 and 31 Dec 2020. Imperial College London is fully committed to the continued success of students from the EU. Candidates who start in 2020 are guaranteed UK-level fees for the entire duration of their course.
Eligible candidates should be motivated, capable of critical and independent thinking, have good oral/written communication skills, like to work in a team and have obtained a master’s (merit or distinction) or bachelor’s (2.1 or first class) degree in engineering, mathematics, physical sciences or life sciences with particular interest in bioinspired approaches to control engineering. Prior experience in computational work using Matlab/Simulink/Python in the context of signal and image processing and/or control theory are desired. Hands-on experiences with mobile robots and/or machine vision are a bonus.
Please contact Prof Krapp firstname.lastname@example.org and Dr Lin email@example.com for inquiries or sending applications including a CV and a one page motivation letter. Applicants should also arrange for two reference letters to be sent to the supervisors.