PhD Student Localization and Mapping in 3D terrains

Om jobbet


For autonomous machines operating in a dynamic environment, it is important to
maintain up-to-date representations of the environment. GNSS solutions provide
near-accurate localisation for machines in large open areas, but perception-based
localisation and mapping is more performant for many safety-critical autonomous
heavy-machine operations, including obstacle detection and avoidance. A key
component is determining the type of perception sensors (cameras, LiDARs,
RADARs) and the sensory configuration in order to accurately estimate the state of
the objects in the environment. The local map from perception-based sensors could


be combined with GNSS estimates to determine the state of a heavy-machine in the
global map during operations. Thus the aim of this project is to investigate
perception solutions that can be utilised to increase efficiency and safety in terms of
obstacle detection and avoidance. The state localisation and mapping project works
in close collaboration with a control systems researcher to develop autonomous
solutions for loader cranes.


We are looking for a skilled state localisation and mapping engineer. We offer a
challenging position in our diversified team of highly qualified engineers.


The job responsibilities


The job responsibilities of the candidate include developing and testing state
estimation algorithms for localisation and mapping of loader cranes in dynamic
environments, working with and testing perception sensors in our closed- and open-
lab environments. The candidate will work in collaboration with a control system
researcher to develop autonomous loader crane operations. In addition, the
candidate is expected to perform research as an Early-Stage Researcher (ESR) in
perception-based localisation and mapping in accordance with the scientific
objectives below.


The scientific objectives include:


1) To provide an expressive yet compact representation of the environment along
with localisation and tracking capabilities. The representation needs to be flexible
and versatile to also accommodate surface parameters to allow for energy-efficient
motion planning and reasoning


2) To allow for a smooth transition between GNSS and perception-based localisation


3) To improve the extraction of dynamic objects and obstacles by utilising previous
knowledge from revisited regions.


The ESR will acquire a broad range of knowledge of the state of the art in related
fields, such as dynamic mapping, state estimation and localisation. The ESR will
also be involved in dissemination through social media promotion of the
MORE-ITN network (an EU Horizon 2020 funded programme), such as surveys,
LinkedIn groups, YouTube video channels, Twitter and blogging.


Knowledge and experiences we are looking for


● Master of Science in Electronics or Computer Science with machine learning
as specialisation
● Enrolled as PhD student in a university with similar research topic
● You are a team player, cooperating and sharing your knowledge with
colleagues
● You like the mix between theory and practical tests on the crane
● You are a self-sufficient problem solver with the ability to promote your ideas


What we offer you


Every employee is equally valuable in the success of HIAB! We are driven by making
people grow and develop, which is why we offer you the opportunity to work with
what you are truly passionate about. We offer both national and international
opportunities and together we build your career path so you constantly are able to
develop and achieve your goals and dreams!


We also have a collective agreement and other benefits like Pension, work time
reduction, Insurances and Wellness grants.


This is a fixed-term employment of 18 months starting November 2022.


At HIAB we believe in growing together!


Interested to join?


Please send your CV and personal letter to: Contact.ControlSystems@hiab.com