Post Doctoral Researcher in Blended Autonomy Vehicles (2 Positions) (# of pos: 2)

Updated: 4 months ago
Location: Limerick, LEINSTER
Deadline: 01 Apr 2021

QUALIFICATIONS:

  • Doctoral degree (level 10) in electronic engineering, software engineering, mechatronics, robotics, automation, computer science, or a related discipline

or

  • Primary degree (Level 8) in a relevant engineering area i.e. electro/mechanical/mechatronics/ robotics and at least 4 years industrial experience in a research role.

OVERALL PURPOSE OF THE JOB:

Combilift Autonomous Systems will see the development of advanced autonomous vehicles for challenging material handling tasks across a wide range of industries.

This collaborative project between Combilift and LERO (CRIS Centre) UL offers an exciting industrial R&D opportunity for two highly motivated research candidates to play a key role in the research, development and testing of vehicle perception systems which will result in the exploration and development of new algorithms for the perception of non-uniform loads and warehouse infrastructure required by intelligent material handling vehicles.

Discovery of suitable vehicle perception systems (sensors and algorithms) for high-fidelity perception of forklift loads including pallets and other non-uniform loads and factory environment surroundings. Such systems do not exist to date and must be researched and built from an optimal choice from the array of newly emerging sensor technologies and processing methods.

The two postdoctoral researchers will work together on the delivery of this project with one researcher focus including safe integration of the autonomy systems within Combilift vehicle designs (and seconded to Combilift). The second postdoc’s research has overlapping objectives with focus on the imaging sensors and processing for real-time auto control.

This project will aid the development of prototype/demonstrator autonomous forklifts in development at Combilift, and this interaction will enable rigorous testing and assessment of developed perception systems in varied warehouse/environment and payload configurations.


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