We’re seeking further contributions for the Complex Systems Toolkit. Please register your interest in developing a resource by 31st July 2026. [LINK TO FORM] You can also join our forthcoming CPD-certificated webinar on ACE-Box and agentic engineering workflows, where we will tell you more about this call for content.
Background
In November 2025 the EPC, with support from Quanser, launched a new Complex Systems Toolkit, aimed at providing accessible, practical resources for embedding complex systems concepts into engineering education.
The Toolkit launched with an abundance of resources, allowing educators and industry professionals to dive into the ‘what’ and ‘how’ of complex systems with knowledge and guidance articles, discover ready-to-use teaching resources including case studies and other classroom activities, and hear directly from the creators and partners who helped shape the Toolkit with a well-attended launch webinar (now available to watch on demand).
These resources have been well used in their first six months, but we’re not stopping there. We want to add further resources, on topics that are emerging as being of vital importance to students as they graduate and seek work. The first of the topics that we want to cover is intelligent robotics.
What, why, and who?
Intelligent robotics, and the more recent applications to physical AI generally, refers to artificial intelligence systems that are embedded in and interact directly with the physical world, rather than operating purely in digital environments. This includes technologies like robots, autonomous vehicles, and drones that can perceive their surroundings through sensors, process that information using AI models, and take real-world actions. Unlike traditional software-based AI, intelligent robotics applications deal with real-time constraints, uncertainty, and complex environments, requiring tight integration between hardware (like sensors and actuators) and decision-making algorithms.
For engineering students, learning about intelligent robotics and physical AI workflows matters because it sits at the intersection of software, hardware, and real-world problem solving. It forces students to grapple with uncertainty, noisy sensor data, timing constraints, and safety considerations, which are unavoidable in real systems like robots or autonomous vehicles. That experience builds practical intuition about how algorithms behave outside ideal conditions. Engineers who understand this are better equipped to design systems that are robust, adaptive, and resilient. Industries are moving rapidly toward automation, robotics, and intelligent infrastructure, so familiarity with intelligent robotics and physical AI workflows opens doors in fields like manufacturing, healthcare technology, and transportation. It helps engineers think holistically: not just “does the code work?” but “does the system behave safely and effectively in the real world?”.
We’re seeking experts in intelligent robotics, from academia, industry, and other engineering organisations, to develop resources on this topic for publication in the Complex Systems Toolkit. These resources will inform, guide and aid educators to embed teaching on intelligent robotics into their engineering lessons, modules or courses.
Contributors sought to develop resources on Intelligent Robotics for inclusion in the toolkit
We invite contributors to develop resources in three areas:
- Knowledge articles: These are resources that users can access to improve their knowledge or find more information. These are intended to provide theoretical and practical background on intelligent robotics concepts and tools such as modelling or decision-making approaches. While guidance articles focus on “how”, knowledge articles focus on “what”.
- Guidance articles: These are resources that users can access to learn how to do something. These are intended to provide practical advice on subjects such as how to explain intelligent robotics to students, or how to assess for skills and competencies in this area. While knowledge articles focus on “what”, guidance articles should focus on “how”.
- Teaching activities: These are resources that users can access to help them know what to integrate and implement. These include use cases/case studies which provide examples of intelligent robotics which can be directly utilised in teaching with the suggested tools, as well as other classroom activities such as coursework, project briefs, lesson plans, demonstration simulations, or other exercises.
We are seeking content on the following topics:
- Robotics and autonomous systems
- Human-robot interaction
- Swarm systems and distributed intelligence
- Edge AI and embedded intelligence
- Cyber-physical systems
- Simulation and digital twins
- Safety, resilience, and uncertainty
- Systems thinking for Intelligent Robotics or Physical AI
- Teaching approaches and assessment methods
We are particularly interested in resources that help engineering educators teach these topics effectively.
Read more about the specific content we are looking for
Submit a knowledge article [LINK TO DOC]
Submit a guidance article [LINK TO DOC]
Submit a teaching activity [LINK TO DOC]
Register your interest
Please register your interest in developing a resource by 31st July 2026. [LINK TO FORM]
If you have already registered an interest and we are expecting your submission, the deadline to submit first drafts is 31st August 2026. Submit your Complex Systems Toolkit Contribution here. Co-authors should complete this form.
If you would like to become a reviewer for the toolkit, please complete this form.
If you would like to suggest links to pages or online resources that we can add to our database of engineering education resources for complex systems teaching, please email Wendy Attwell.
Additional information
In undertaking this work, contributors will become part of the growing community of educators who are helping to ensure that tomorrow’s engineering professionals have the complex systems skills, knowledge, and attributes that they need to provide a better future for us all. Contributors will be fully credited for their work on any relevant Toolkit materials and will be acknowledged as authors should the resources be published in any form. Developing these resources will provide the chance to work with a dynamic, diverse and passionate group of people leading the way in expanding engineering teaching resources, and may help in professional development, such as preparing for promotion or fellowship.
Learn more about the Complex Systems Toolkit
Those interested in contributing to the Complex Systems Toolkit should fill out this form and we will be in touch.
Hear from our Working Group Co-Chairs on why you should get involved.
Learn more about the Complex Systems Toolkit,here.
Learn more about the members of the Complex Systems Toolkit Working Group, here.