Robot Technology


An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on two or more axes. People and animals can effectively manipulate objects of many shapes, sizes, weights, and materials using a variety of primitives such as grasping, pushing, sliding, tipping, rolling, and throwing. In contrast, industrial robots manipulate objects by pick-and-place, but it is still challenging to identify and approach objects in an uncertain environment, and also to determine a proper manipulation method towards different types of objects. To complete these kinds of tasks, some basic but not very specific steps need to follow: firstly, pinpoint the location of an object and obtain its world coordination in a world coordinate system; secondly, drive the whole robot towards the targeted object and adjust its posture for object pick-up; thirdly, drive the joints of robotic arm to pick up the objects for manipulation or put it to a targeted location as required.


The goal of the coursework is to apply your knowledge and practical skills to solve real-world problems in a virtual environment (i.e. V-rep). This coursework is to design and improve the performance of object manipulation via a mobile robot, e.g. Kuka Youbot, which localises a targeted object and drives the robots toward it for specific manipulating. The tasks include implementation of the basic functionalities based on the lab tutorials (week 3-6) and attempts of advanced ones for your potential contribution.

Basic functionalities

This part is based on the last part of V-rep tutorials, and exact tasks include:

  • Object localisation from a given position
  • Adjust the robot towards the target objects based on the orientation difference between the object and robot
  • Drive the robot towards the objects and keep a proper distance for object manipulation.
  • Drive the robot’s joints to pick up the object

Advanced functionalities

This is an advanced part, requiring the localisation of the object via sensing technologies, such as cameras. It enables you to deeply understand the environmental sensing technology and inspire you to adopt intelligent algorithms to optimise your manipulation with different settings.

  • Processing sensory information
  • Making decisions on the sensory information
  • Adjust robot’s gesture according to the real-time input from the environment

The coursework should be finished individually.. And of course, feel free to discuss your ideas with them during office hours. Here are suggestions for getting started on projects:

  • Familiar with basic kinematic structure of the Kuka Omnirob in V-rep, including the controllable joints and wheels. It can be done through a default GUI of Ominrob in V-rep. Most of the related knowledge would be covered introduced during the remaining tutorials. Use these tutorials to get familiar with robotic manipulation skills.
  • Familiar with the programing skill for the V-rep using the Lau scripts. It allows you to get the current position of the robot and then determine the distance between two objects. This measurement will be covered in the tutorial.
  • Feel free to test the available sensors in V-rep, and master the data acquisition skills from sensors. Try to understand the how to programme to transfer the sensory data to a specific control command of the robots. You may also want to compare how the parameter setting influences the sensory data.

Your final report should address but not limit each of the following:

  • Introduction: Define and motivate the problem, discuss background material, describe the problem you plan to solve and give a basic outline of what you propose to implement.
  •  Include any formulas, pseudo code, and diagrams — anything that is necessary to clearly explain your system and what you have done. If possible, illustrate the intermediate stages of your approach with results images.
  •  Clearly describe your experimental protocols. If you are using training and test data, report the numbers of training and test images. Be sure to include example output figures. Quantitative evaluation is always a big plus (if applicable).
  •  Summarize the main insights drawn from your analysis and experiments. You can get a good project grade even with negative results, as long as you show evidence of extensive exploration, thoughtfully analyse the causes of your negative results, and discuss potential solutions.
  •  including conference papers, journal papers, and URLs for any external code or data used.


Grades will be based on the quality of the project (originality, thoroughness, extent of analysis, etc.) and the clarity of the written report. Ideally, you will try something new or apply ideas from class to your domain or research. You can still get a good grade if your ideas do not work out, as long as your report show evidence of extensive analysis and exploration, and provides thoughtful explanations of the observed outcomes.

Criteria  Description  %  
Introduction  Appropriate description and understanding of the given problemComprehensive discussion of the state of the art, with examples of the solution chosen in recent research projects10%
ApproachClear description of the chosen approach Justification behind the chosen solution is well substantiated and is appropriate to the given problemClear description of your contribution15%
Results Analysis 
  Clear description of the achievement procedure of the experimentClear explanation of the experimental results20%
Discussion and conclusionsEvaluation of the performance of the chosen approach Issues encountered are described and solutions/actions taken discussedAlternative solutions and suggestions for improvement are presented15%
ReferencesLinks, conference papers, journal papers, etc.  in the IEEE reference format10%
Sensory Implementation (advanced)The use of sensors to get the location of an object10%
Sensory feedback (advanced)The use of real-time sensory feedback to adjust robotic manipulation10%
Advance Intelligent Algorithms  (advanced)Apply intelligent algorithms to plan the movement of the robot.10%

Submission instructions

The final report should be submitted in PDF format. It should be (the equivalent of) 2500.  Here is a rough outline to follow for the report:

  • A single compressed file with your student ID (for example: needs to be updated into the Dropbox.
  • The zipped file should contain three folders: “Source”, “Video” and “Report”. The “Video” folder should contain a short video showing the robot moving around to pick and place the object. The “Report” folder can contain the reports (named according to your Student ID, e.g.: UP123456.pdf).
  • The report should be in the IEEE journal format. The templates, including word and latex formats, are available to download in the Moodle.

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