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...	...	@@ -4,11 +4,15 @@
4	4
5	5	//(left) a railbike, the foundation of the upcoming autonomous draisine & (right) a stripped down [[LGB>>https://www.lgb.de/lp/20/willkommen-bei-lgb]] engine for a 45mm model track.//
6	6
	7	+{{info}}
	8	+Kick-off meeting on Monday 7th Oct. at 10am in room 1115 CAP4
	9	+{{/info}}
	10	+
7	7	== Overview of topics (WIP) ==
8	8
9	9	**The solutions in all topics must be scalable for both demonstrators!**
10	10
11		-~1. An end-user app and management system for on-demand train service
	15	+~1. An end-user app and management system for on-demand train service **[(partially) reserved]**
12	12	// This topic may be split up into two theses (app & management)//
13	13
14	14	* A mobile app to call a train to a desired location and communicate desired destination
...	...	@@ -26,22 +26,40 @@
26	26	* Safe behavior model generation using PASTA ([[https:~~/~~/marketplace.visualstudio.com/items?itemName=kieler.pasta>>https://marketplace.visualstudio.com/items?itemName=kieler.pasta]])
27	27	* Assumes preprocessed sensor input and destination determination (see other topics)
28	28
29		-3. AI-based image recognition for autonomous train control
	33	+3. AI-based obstacle detection for autonomous train control using image recognition
30	30	// This topic will be jointly advised with the AG Distributed Systems//
31	31
32		-* Sensor processing of a train mounted camera
33		-* Obstacle detection at speeds up to 50 km/h
	36	+* Sensor processing of a train-mounted camera to detect objects (potential obstacles)
	37	+* Tasks will involve:
	38	+** Sensor mounting on the demonstrator
	39	+** Collection of data (images, videos)
	40	+** Labeling of data to enable training (esp. for small scale model)
	41	+** Training of AI
	42	+** Evaluation of quality
	43	+** Live testing
	44	+* Step-wise evaluation of the influence of vehicle speed on the detection quality
	45	+* Evaluate applicability and influence of training data due to different environments for the demonstrators (i.e. indoors vs. outdoors)
	46	+* (Optional) Trajectory detection to categorize safety threads of moving obstacles
	47	+* (Optional) Evaluate performance on different hardware, e.g. Rasberry Pi vs. AI hardware
	48	+* (Optional) Test and evaluate on the edge deployment
	49	+* For interfacing with the controller, the sensor should provide an assessment how safe the area in front of the train is, such that the controller can adjust its speed.
34	34	* Potential hardware (subject to changes):
35	35	** [[https:~~/~~/www.raspberrypi.com/documentation/accessories/camera.html>>https://www.raspberrypi.com/documentation/accessories/camera.html]]
36	36	** (((
37	37	[[https:~~/~~/www.axis.com/de-de/products/axis-p1455-le>>https://www.axis.com/de-de/products/axis-p1455-le]]
38	38	)))
39		-* [Optional] Distance measuring using multiple cameras
40	40
41		-4. AI-based sensor processing for autonomous train control
	56	+4. Classic and AI-based distance sensing for autonomous train control using different sensors **[already reserved]**
42	42	// This topic will be jointly advised with the AG Distributed Systems//
43	43
44		-* Sensor processing of train mounted LiDAR or ultrasonic sensor
	59	+* Explore and evaluate different sensors and processing techniques for distance measuring in rail vehicles
	60	+* Compare quality, ranges, and reliability w.r.t speed and size (demonstrator)
	61	+* Sensors and approaches:
	62	+*1. Ultrasonic sensor
	63	+*1. Single camera with AI image recognition
	64	+*1. (Multiple cameras)
	65	+*1. (LiDAR)
	66	+*1. (Sensorfusion)
45	45	* Potential hardware (subject to changes):
46	46	** [[https:~~/~~/www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm>>https://www.elektronik-kompendium.de/sites/praxis/bauteil_ultrasonic-hcsr04p.htm]]
47	47	** [[https:~~/~~/www.pi-shop.ch/lidar-ld06-lidar-module-with-bracket-entwicklungskit-fuer-raspberry-pi-sbc>>https://www.pi-shop.ch/lidar-ld06-lidar-module-with-bracket-entwicklungskit-fuer-raspberry-pi-sbc]]
...	...	@@ -48,18 +48,38 @@
48	48	** (((
49	49	[[https:~~/~~/www.blickfeld.com/de/produkte/cube-1/>>https://www.blickfeld.com/de/produkte/cube-1/]]
50	50	)))
51		-* Obstacle detection at speeds up to 50 km/h
52		-* Distance measuring (ultrasonic sensor)
53	53
54	54	5. A digital twin for an autonomous on-demand train service **[already reserved]**
55		- // Note: Tight interfacing with other topics//
	75	+// Note: Tight interfacing with other topics//
56	56
57	57	* A digital twin for an autonomous passenger train
58	58	* Monitoring system for the state and location of the vehicle
59		-* Remote control capabilities //(interfacing with controller)//
	79	+* Simulation capabilities to test and replay behavior (virtual environment)
60	60	* Monitoring and economic analysis of on-demand service operation (//integration/interfacing of management system//)
61	61	* Reliability analysis/statistics to ensure transparency of autonomous operation
62	62
	83	+6. Remote control for rail vehicles
	84	+//Note: Tight interfacing with other topics//
	85	+
	86	+* Remote control of speed and brakes //(interfacing with controller)//
	87	+* Live streaming of camera data and other sensors
	88	+* Evaluation and setup of a wireless communication network with a high reliability
	89	+* (Optional) Construction of a [[remote control panel>>https://cloud.rz.uni-kiel.de/index.php/s/jCxitwKzddqEctD]]
	90	+* (Optional) Augmented reality integration to simulate training scenarios
	91	+
	92	+7. A standalone sensor box for monitoring rail vehicles **[already reserved]**
	93	+//This prototype will be tested (only) using the full-scale demonstrator and is intended for monitoring non-autonomous vehicles (not the REAKTOR)//
	94	+
	95	+* Development of a sensor array to monitor rail vehicle operation
	96	+* It should serve as a plugin solution inside the train's cockpit for monitoring operation and as preparation for autonomous control
	97	+* Design for wireless communication of collected data
	98	+* Possible sensors:
	99	+** GPS
	100	+** Accelerometer
	101	+** Camera
	102	+* Analysis of data for autonomous driving
	103	+* Potential integration into digital twin infrastructure
	104	+
63	63	== Goals ==
64	64
65	65	* TBA for each topic individually