| Task ID | Points | Assignment | Due date 1) |
|---|---|---|---|
| Robot locomotion and sensing (8 pts) | |||
| Task01 | 3 | Open-loop locomotion control | 13. 10. 2018 |
| Task02a | 3 | Reactive obstacle avoidance | 20. 10. 2018 |
| Task02b | 2 | Map building | 27. 10. 2018 |
| Grid-based planning (8 pts) | |||
| Task03 | 3 | Grid based path planning | 27. 10. 2018 |
| Task04 | 5 | Incremental path planning (D* Lite) | 03. 11. 2018 |
| Randomized sampling-based planning (15 pts) | |||
| Task05 | 6 | Randomized sampling-based algorithms | 17. 11. 2018 |
| Task06 | 5 | Curvature-constrained local planning in RRT | 24. 11. 2018 |
| Task07 | 4 | Asymptotically optimal randomized sampling-based path planning | 01. 12. 2018 |
| Multi-goal path planning (14 pts) | |||
| Task08 | 4 | Multi-goal path planning and data collection path planning - TSP-like formulations | 01. 12. 2018 |
| Task09a | 3 | Data collection path planning - obstacle aware planning | 08. 12. 2018 |
| Task09b | 4 | Data collection path planning with remote sensing (TSPN) - decoupled approach | 08. 12. 2018 |
| Task09bonus | - | Data collection path planning with remote sensing (TSPN) - sampling-based approach (5 bonus points) | 08. 12. 2018 |
| Task10 | 3 | Data collection path planning with curvature-constrained trajectory - Dubins TSP with Neighborhoods (DTSPN) - decoupled approach | 15. 12. 2018 |
| Task10bonus1 Task10bonus2 | - | DTSP - ETSP+AA and plan execution (5 bonus points) Bounds for the DTSPN using GDIP and sampling-based approach (5 bonus points) | 13. 01. 2019 |
| Game theory in robotics (15 pts) | |||
| Task11 | 3 | Greedy policy in pursuit-evasion | 15. 12. 2018 |
| Task12 | 6 | Monte Carlo Tree Search policy in pursuit-evasion | 13. 01. 2019 |
| Task13 | 6 | Value-iteration policy in pursuit-evasion | 13. 01. 2019 |
Sum points: 60; Bonus points: 15
Total max points: 75