PurpleSand
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README.md
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ββ.npy # Sketch instructions
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```
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---
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## Dataset Overview π
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"drive_map_name": "occupancy_map",
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"model_guideline": "You are an indoor food-serving robot.\n\nYou must follow these driving instructions:\n1. You must avoid collisions.\n2. You should prioritize reaching the final destination.\n3. You should follow the Trajectory Instruction.\n a. If the Trajectory Instruction cannot be followed due to any obstacles, you should deviate to bypass the obstacle.\n b. You should try to evade any identifiable obstacles.\n4. You should maintain a constant driving speed."
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}
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```
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ββ.npy # Sketch instructions
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```
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How to extract the dataset:
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```bash
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# To recombine the parts, use:
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cat COMMAND_part_* > COMMAND.tar.zst
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# Then decompress the archive:
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tar --use-compress-program=zstd -xf COMMAND.tar.zst
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```
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---
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## Dataset Overview π
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"drive_map_name": "occupancy_map",
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"model_guideline": "You are an indoor food-serving robot.\n\nYou must follow these driving instructions:\n1. You must avoid collisions.\n2. You should prioritize reaching the final destination.\n3. You should follow the Trajectory Instruction.\n a. If the Trajectory Instruction cannot be followed due to any obstacles, you should deviate to bypass the obstacle.\n b. You should try to evade any identifiable obstacles.\n4. You should maintain a constant driving speed."
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}
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```
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## Citation
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If you find this work useful, please cite our paper:
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```
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@article{choi2024canvas,
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title={CANVAS: Commonsense-Aware Navigation System for Intuitive Human-Robot Interaction},
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author={Choi, Suhwan and Cho, Yongjun and Kim, Minchan and Jung, Jaeyoon and Joe, Myunchul and Park, Yubeen and Kim, Minseo and Kim, Sungwoong and Lee, Sungjae and Park, Hwiseong and others},
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journal={arXiv preprint arXiv:2410.01273},
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year={2024}
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}
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```
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