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====== Tasks ======

^ Task ID ^ Points ^ Assignment ^ Due date ((All task deadlines are **23:59 PST**))^
^ Robot locomotion and sensing (8 pts) ^^^^
| [[courses:b4m36uir:hw:task01|Task01]] |  3  | Open-loop locomotion control |  13. 10. 2018  |
| [[courses:b4m36uir:hw:task02a|Task02a]] |  3  | Reactive obstacle avoidance |  20. 10. 2018  |
| [[courses:b4m36uir:hw:task02b|Task02b]] |  2  | Map building |  27. 10. 2018  |
^ Grid-based planning  (8 pts) ^^^^
| [[courses:b4m36uir:hw:task03|Task03]] |  3  | Grid based path planning  |  27. 10. 2018  |
| [[courses:b4m36uir:hw:task04|Task04]] |  5  | Incremental path planning (D* Lite) |  03. 11. 2018  |
^ Randomized sampling-based planning (15 pts) ^^^^
| [[courses:b4m36uir:hw:task05|Task05]] |  6  | Randomized sampling-based algorithms  |  17. 11. 2018  |
| [[courses:b4m36uir:hw:task06|Task06]] |  5  | Curvature-constrained local planning in RRT  |  24. 11. 2018  |
| [[courses:b4m36uir:hw:task07|Task07]] |  4  | Asymptotically optimal randomized sampling-based path planning  |  01. 12. 2018  |
^ Multi-goal path planning (14 pts) ^^^^
| [[courses:b4m36uir:hw:task08|Task08]] |  4  | Multi-goal path planning and data collection path planning - TSP-like formulations |  01. 12. 2018  |
| [[courses:b4m36uir:hw:task09|Task09a]] |  3  | Data collection path planning - obstacle aware planning   |  08. 12. 2018  |
| [[courses:b4m36uir:hw:task09|Task09b]] |  4  | Data collection path planning with remote sensing (TSPN) - decoupled approach  |  08. 12. 2018  |
| [[courses:b4m36uir:hw:task09|Task09bonus]] |  -  | Data collection path planning with remote sensing (TSPN) - sampling-based approach (**<fc #ff0000>5 bonus points</fc>**)  |  08. 12. 2018  |
| [[courses:b4m36uir:hw:task10|Task10]] |  3  | Data collection path planning with curvature-constrained trajectory - Dubins TSP with Neighborhoods (DTSPN) - decoupled approach  |  15. 12. 2018  |
| [[courses:b4m36uir:hw:task10bonus1|Task10bonus1]] [[courses:b4m36uir:hw:task10bonus2|Task10bonus2]] |  -  | DTSP - ETSP+AA and plan execution (**<fc #ff0000>5 bonus points</fc>**) \\ Bounds for the DTSPN using GDIP and sampling-based approach (**<fc #ff0000>5 bonus points</fc>**)  |  13. 01. 2019  |
^ Game theory in robotics (15 pts)  ^^^^
| [[courses:b4m36uir:hw:task11|Task11]] |  3  | Greedy policy in pursuit-evasion  |  15. 12. 2018  |
| [[courses:b4m36uir:hw:task12|Task12]] |  6  | Monte Carlo Tree Search policy in pursuit-evasion  |  13. 01. 2019  |
| [[courses:b4m36uir:hw:task13|Task13]] |  6  | Value-iteration policy in pursuit-evasion  |  13. 01. 2019  |


Sum points: **60**; Bonus points:  **<fc #ff0000>15</fc>**

**Total max points: 75**