ACS6334 Mobile Robotics and Autonomous Vehicles

Module Description

Recent research is finally leading to real advances in applications of mobile robotics and autonomous vehicles. The DARPA Grand Challenges have demonstrated the potential for fully autonomous road vehicles leading to major car companies undertaking trials of driverless cars. Unmanned aerial vehicles are routinely being deployed for a variety of applications including natural disaster search and rescue. The Curiosity rover is exploring the surface of Mars and unmanned underwater vehicles can navigate whole oceans. The technological challenges of developing such autonomous systems are varied and complex. This module introduces the concepts of autonomous vehicles and mobile robotics focussing on the control and systems engineering issues related to autonomous operation. The module covers basic concepts in robot architectures, kinematic and dynamic modelling, control and decision making. Topics such as path planning, navigation, obstacle avoidance, simultaneous localisation and mapping (SLAM), sensors, state estimation and agent methods will be covered. Applications and techniques associated with single, co‐operative and swarming robotics will be covered with case studies demonstrating real world applications of the techniques and algorithms.

Credits: 10 (Spring semester)

Module Leader

Dr Roderich GrossDr Roderich Gross
Room F09, Pam Liversidge Building

If you have any questions about the module please talk to me during the lectures or the labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask questions.

Outside of lectures please contact me via email.

Learning Outcomes

Learning Outcomes

By the end of the module students will:

  1. Classify robots by their autonomy levels and explain the technical issues that define the autonomy level. Design control architectures and the importance of high level versus low level control and explain these in the context of real world applications. [EA2p]
  2. Compare different software architectures and appraise different locomotion methods in mobile robotics applications. Derive and apply kinematic and dynamic models for mobile robots and vehicles. [EA1p]
  3. Explain the features of different sensors commonly used in autonomous vehicles and mobile robotics. Create and evaluate controller solutions applying these in real-world scenarios. [EA4p]
  4. Apply and analyse fundamental methods in mobile robotics, such as motion planning, obstacle avoidance, localization and mapping. [EA3m]
  5. Critically appraise research advances in autonomous and distributed robotics, including decentralised control and learning. [EA3m]

This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage.



  • Performance metrics, kinematic and dynamic models of vehicles
  • Autonomy and its levels
  • Locomotion in applications: legged, wheeled and hybrid robots
  • Motion control methods
  • Sensors on mobile robots
  • Navigation and data fusion
  • Dynamical state estimation methods
  • Navigation of ground
  • Aerial, underwater and space vehicles
  • Simultaneous localisation and mapping
  • Path planning and obstacle avoidance
  • Reconfigurable robots
  • A* method, basics of swarm robotics
  • Cooperative robots
  • Evolutionary robotics
  • Software architectures for robots
  • Reactive, behavioural
  • Three layered architectures
  • Belief-desire-intention agents
  • High level programming of robots
  • Agent oriented programming
  • Practical choices for applications

Teaching Methods

Learning and Teaching Methods

Lectures: 16 hours
Tutorials: 4 hours
Laboratory Classes (including associated assessment): 8 hours
Independent Study: 72 hours

Teaching Materials

Learning and Teaching Materials

All teaching materials will be available via MOLE.



The module is assessed through:

  • 2 hour formal exam 60%
  • Lab work and associated assignments 40%


2 sets of questionnaires: one after lecture 8 and one after lecture 16 will be assessed with feedback. Verbal feedback will be provided during 4 tutorials.

Student Evaluation

Student Evaluation

Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module.

Recommended Reading

Recommended Reading

  • Kozlowski, K.R., Modelling and Identification in Robotics (Advances in Industrial Control), Springer, 1998, ISBN 3-540-76240-X
  • Kelly, A., Mobile Robotics: Mathematics, Models, and Methods, Cambridge University Press, 2013, ISBN 978-1-107-03115-9
  • River Edge, N.J., Active sensors for local planning in mobile robotics, London: World Scientific, 2001, ISBN 9810246811 [Available in Portobello, 629.892 (A)]