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Funded PhD Opportunity

Autonomous Object Recognition for Robots

Subjects: Computer Science and Informatics and Computer Science and Informatics


Summary

The advancement in robotic technology has prompted the investigation of developing solutions to assist humans in performing ordinary tasks in everyday settings. A robot must have the ability to interact with its environment and identify different objects required to autonomously complete a given task. Within this context, an important skill a robot should acquire is the ability to successfully interact with objects of varying size, shape, etc. To do this, a robot should have the ability to utilise prior knowledge in identifying objects interacted with before, while having the ability to learn new objects by identifying key characteristics from these unseen objects. Reliable object detection and recognition is a difficult task for robots to achieve and, therefore, still remains a challenge when real-world environments are considered. Curiosity, often seen in humans and its primates, drives learning activities. These activities allow them to acquire knowledge and skills that can be exploited when completing different tasks.

The main objective of the project will be to leverage this concept by developing intelligent algorithms for robot manipulator platforms, that will have the ability to investigate unknown objects by determining the object properties and affordances and learn the object using curiosity-driven cumulative learning. Identifying novel objects in an environment and visually extracting characteristics and features required for the cumulative learning of objects is useful towards identifying what the object can be used for. Primarily, 2D/3D vision processing techniques will be utilised in identifying an object’s properties and affordances. Although very effective, vision cannot explore certain characteristics of an object.

Further characteristics can be learned through physical manipulation of the object using tactile sensing. Tactile sensing technology has improved greatly in recent years, resulting in some tactile sensors capable of sensing with accuracies comparable to human fingertips. In this project, tactile sensing will be employed to complement the robot’s ability to visually determine object properties and affordances. The capability of utilising both sensor modalities will allow for effective analysis and manipulation of novel objects. Following extraction of features through both vision and tactile sensing, machine learning techniques will be used to enable a robot to identify already known objects and cumulatively learn about objects in different scenarios. Once familiar with objects, the robot will identify which object should be used to complete intricate tasks that would be useful in an assistive living environment.

This project will make use of the robotics equipment available in the Intelligent Systems Research Centre robotics lab, specifically the PR2 mobile manipulator robot, equipped with 2D/3D vision sensors and end effectors fitted with state-of-the-art biotac tactile sensors.


Essential criteria

  • To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
  • Research proposal of 1500 words detailing aims, objectives, milestones and methodology of the project
  • A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 70%
  • For VCRS Awards, Masters at 75%
  • Publications - peer-reviewed
  • Experience of presentation of research findings
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Vice Chancellors Research Studentship (VCRS)

    Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Bursary (VCRB)

    Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    Fees only award (PhD fees + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 15,009 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies


Other information


The Doctoral College at Ulster University


Reviews

Profile picture of Adrian Johnston

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

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Key dates

Submission deadline
Friday 7 February 2020

Interview Date
23 to 24 March 2020


Applying

Apply Online  


Campus

Magee campus

Magee campus
A key player in the economy of the north west


Contact supervisor

Dr Bryan Gardiner


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