PhD Study : Autonomous Object Recognition for Robots

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

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• 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 and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) 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.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living