Case Study booklet 2024 - Rescue Robots (Required for HL paper 3)
Introduction
By next May, you need to have THOROUGHLY RESEARCHED and UNDERSTAND the casae study booklet: Research Robots. The Case Study is not an explanation or a text-book, but rather a description of a problem to be STUDIED and INVESTIGATED. After doing some RESEARCH and READING, your level of understanding should become considerably deeper.
Deep sea Robot Victor 6000
Structure of the paper
30 marks, 60 minutes, worth 20% of your final CS grade.
3 x Short answer questions worth ~6 marks and ~12 minutes each
Command terms: Define (2 marks), Outline (2 marks), Explain (4 marks), Describe (4 marks)
Compare, evaluate, discuss, to what extent
1 x Extended answer question worth 12 marks - 24 minutes
Through their investigation of the case study, students should be able to:
demonstrate an understanding of the computer science concepts fundamental to the system(s) in the case study (objective 1)
demonstrate an understanding of how the system(s) in the case study work (objective 1)
apply material from the course syllabus in the context of the case study (objective 2)
explain how scenarios specified in the case study may be related to other similar local and global scenarios (objective 3)
discuss the social impacts and ethical issues relevant to the case study (objective 3)
explain technical issues relating to the case study (objective 3)
evaluate information that may be gathered from local and global sources including field trips, interviews, primary and secondary research, invited guest speakers and online interviews (objective 3)
evaluate, formulate or justify strategic solutions based on the synthesis of information from the case study itself, additional research and new stimulus material provided in the examination paper (objective 3).
Bundle adjustment
Computer vision
Dead reckoning data
Edge computing
Global map optimization
Global positioning system (GPS) signal
GPS-degraded environment
GPS-denied environment
Human pose estimation (HPE)
Inertial measurement unit (IMU)
Keyframe selection
Key points/pairs
Light detection and ranging (LIDAR)
Object occlusion
Odometry sensor
Optimization
Relocalization
Rigid pose estimation (RPE)
Robot drift
Simultaneous localization and mapping (SLAM)
Sensor fusion model
Visual simultaneous localization and mapping (vSLAM) modules:
- Initialization
- Local mapping
- Loop closure
- Relocalization
- Tracking
YouTube videos
Further links