[AllUsers-ISR] Call for Tenders for PhD Research Grant - Ref. BD4/2023/Topic 2 - Integration of 6D object pose estimation and environment representation with motion planning strategies for fine object grasping using mobile robots. Deadline: 15th October

[Lara Costa]

Call for Tenders for PhD Research Grant – Ref. BD4/2023/Topic 2 -
Integration of 6D object pose estimation and environment representation with
motion planning strategies for fine object grasping using mobile robots.

The Institute of Systems and Robotics (ISR-UC) is calling for applications
for ONE PhD Research Grant in the area of Electrical Engineering and
Intelligent Systems, or Electrical and Computer Engineering, under the FCT
Research Grant Regulations (RBI) and the Research Grant Holder Statute
(EBI).

The scholarships will be funded by the Foundation for Science and Technology
(FCT) under the Collaboration Protocol for Funding the Multi-Year Plan for
Research Scholarships for PhD Students, signed between the FCT and the R&D
Unit, Institute of Systems and Robotics, UID/EEA/00048/2020.

 

The aim is to explore object detection in an industrial environment and
subsequent pick-and-place operations performed by a mobile robot. Machine
learning methods will be applied to process multimodal data in robotic
perception components and reinforcement learning to learn actions. The work
plan consists of the following tasks:

 

1.       Research into 6D object pose estimation based on visual and/or
depth sensor data. Deep Learning-based approaches have shown superior
performance in object segmentation and point matching and general
robustness, while geometric approaches tend to be more accurate (more
refined optimisation) and more efficient. In this task, a hybrid approach
will be followed.

 

2.       Specialisation of models in warehouse/industrial contexts.   In
particular, the detection of pallets and the estimation of their 6D pose, in
an industrial context, for navigation applications (pick-and-place) using
robotic platforms (e.g. forklifts).

 

3.       Research into navigation using reinforcement learning on the best
behaviour a robotic platform should have when approaching objects for
loading, including possible risk situations/scenarios and behaviours to
minimise location errors.  The aim is to use 6D object information to
improve the robot's state representation (afordance-based and
representation/image-based), so that it learns behaviours that avoid
collisions, guarantee the platform's safety and allow it to autonomously
choose the best docking/picking behaviours.

 

4.       Exploration and experimental evaluation in an indoor context and in
a semi-structured context with the aim of validating the proposed
methodologies.

 

Supervisors: Prof Urbano Nunes, Prof João Barreto, Prof Rui Araújo.

 

The competition is open between 1 October 2023 and 23:59 (Lisbon time) on 15
October 2023.

Applications and supporting documents must be submitted by email to
<mailto:lara at isr.uc.pt> lara at isr.uc.pt, quoting reference BD4/2023/Topic 2.


 

For further information  please see:  <https://www.euraxess.pt/jobs/148028>
https://www.euraxess.pt/jobs/148028 

 

Cumprimentos,

 

Lara Costa

Gestora de Ciência

Instituto de Sistemas e Robótica

Departamento de Engenharia Eletrotécnica e de Computadores

Rua Sílvio Lima, Pólo II, Universidade de Coimbra

3030-790 Coimbra

Tel: 239 796 217 (Ext: 421113)

 

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