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Module: Hardware and Sensing Technologies (Part1)
| 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/Attitudes: • 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. |
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| 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. |
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| 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. |
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| AI involvement | Yes — 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. | |
| References to literature | Lee, E. A., & Seshia, S. A. (2020). Introduction to Embedded Systems (3rd ed.). MIT Press. Kopetz, H. (2011). Real‑Time Systems: Design Principles for Distributed Embedded Applications (2nd ed.). Springer. Isermann, R. (2017). Mechatronic Systems: Fundamentals. Springer. Raj, A., & Saxena, P. (2022). Emerging trends in autonomous systems hardware integration. IEEE Access, 10. Thrun, S. (2010). Toward robotic cars. Communications of the ACM, 53(4). NIST SP 800‑161 (2020). Supply Chain Risk Management Practices for Federal Information Systems and Organizations. |
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| Lab equipment | Yes | |
| Virtual lab | Yes | |
| MOOC course | ||
