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Module: Hardware and Sensing Technologies (Part 1)

Study level Bachelor
ECTS credits 1 ECTS
Study forms Hybrid or fully online
Module aims Provide a practical foundation in embedded protocols, sensing hardware, and navigation/positioning for autonomous systems. Students will learn how sensors (IMU, GNSS, LiDAR/camera), actuators and power systems connect to embedded computing units via standard buses (I²C, SPI, UART, CAN/CAN-FD, Ethernet/DDS), how data moves deterministically across the system, and how to calibrate, time-synchronise and validate multi-sensor setups. Emphasis is placed on interface compatibility, thermal/power constraints, EMC considerations and the integration lifecycle (from requirements to HIL testing) that turns components into a reliable platform.
Pre-requirements Basic electronics (Ohm’s law, signals, voltage/current levels), programming fundamentals (preferably C/C++ or Python), and introductory control/linear algebra (vectors, matrices). Ability to use a Linux-based toolchain and Git is beneficial. Prior exposure to microcontrollers or SBCs (e.g., STM32, Arduino, Raspberry Pi, Jetson) is helpful but not mandatory.
Learning outcomes Knowledge
• Explain operating principles and specs of common sensors (IMU, GNSS, range and vision sensors) and actuators.
• Describe embedded communication protocols (I²C, SPI, UART, CAN/CAN-FD, Ethernet, DDS) and timing/synchronisation concepts.
• Outline the hardware integration lifecycle, calibration methods, environmental/EMC testing, and safety/quality standards.
Skills
• Select appropriate sensors/computing units for a given task and justify trade-offs of accuracy, latency, power and cost.
• Configure and bring up device buses, log and interpret sensor data, and perform basic multi-sensor calibration.
• Build a minimal HIL test to validate a perception/control loop and document results.
Understanding
• Recognize integration risks (interface incompatibility, EMI, thermal/power limits) and propose mitigations.
• Appreciate supply chain constraints and obsolescence planning when choosing components.
• Work safely, ethically and reproducibly, documenting configurations and changes.
Topics Sensors, Computing Units, and Navigation Systems:
• Sensor taxonomy and specs (IMU, GNSS, magnetometer, LiDAR, depth, camera); calibration (extrinsics/IMU alignment).
• Embedded computing: MCUs vs. SoCs (CPU/GPU/accelerators), power/thermal design, memory and I/O.
• Navigation and positioning: GNSS/IMU basics, odometry, sensor fusion concepts.
Embedded Protocols and Communication Backbones:
• I²C/SPI/UART fundamentals; CAN/CAN-FD; Ethernet, TSN concepts; DDS/ROS 2 communications.
Integration Lifecycle and Reliability:
• Requirements → interface design → assembly → HIL/SIL → environmental & EMC testing; timing/synchronisation; redundancy.
Supply Chain & Lifecycle Considerations:
• Component availability, quality/traceability, cybersecurity (SBOM/firmware signing), and obsolescence planning.
Type of assessment The prerequisite of a positive grade is a positive evaluation of module topics and presentation of practical work results with required documentation
Learning methods Lecture — Concept overviews with worked hardware schematics and bus timing examples.
Lab works — Hands-on bring-up of sensors and a microcontroller/SBC, bus sniffing, timestamping and calibration; mini HIL demo.
Individual assignments — Short design/calculation tasks (component selection, interface budgets) with a brief technical note.
Self-learning — Curated readings and datasheets; recommended MOOC videos to reinforce embedded and navigation concepts.
AI involvement Assisted code scaffolding and debugging, log summarisation, data analysis/visualisation and literature search support. Students must verify outputs, cite use of AI tools, and avoid uploading proprietary or assessment-sensitive data.
Recommended tools and environments
Verification and Validation focus
Relevant standards and regulatory frameworks
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