Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.18385 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916416930709504 |
|---|---|
| author | Hidalgo, Rafael Parron, Jesse Varde, Aparna S. Wang, Weitian |
| author_facet | Hidalgo, Rafael Parron, Jesse Varde, Aparna S. Wang, Weitian |
| contents | This paper presents a system called Robo-CSK-Organizer that infuses commonsense knowledge from a classical knowledge based to enhance the context recognition capabilities of robots so as to facilitate the organization of detected objects by classifying them in a task-relevant manner. It is particularly useful in multipurpose robotics. Unlike systems relying solely on deep learning tools such as ChatGPT, the Robo-CSK-Organizer system stands out in multiple avenues as follows. It resolves ambiguities well, and maintains consistency in object placement. Moreover, it adapts to diverse task-based classifications. Furthermore, it contributes to explainable AI, hence helping to improve trust and human-robot collaboration. Controlled experiments performed in our work, simulating domestic robotics settings, make Robo-CSK-Organizer demonstrate superior performance while placing objects in contextually relevant locations. This work highlights the capacity of an AI-based system to conduct commonsense-guided decision-making in robotics closer to the thresholds of human cognition. Hence, Robo-CSK-Organizer makes positive impacts on AI and robotics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_18385 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robo-CSK-Organizer: Commonsense Knowledge to Organize Detected Objects for Multipurpose Robots Hidalgo, Rafael Parron, Jesse Varde, Aparna S. Wang, Weitian Robotics Artificial Intelligence I.2.6; I.2.9 This paper presents a system called Robo-CSK-Organizer that infuses commonsense knowledge from a classical knowledge based to enhance the context recognition capabilities of robots so as to facilitate the organization of detected objects by classifying them in a task-relevant manner. It is particularly useful in multipurpose robotics. Unlike systems relying solely on deep learning tools such as ChatGPT, the Robo-CSK-Organizer system stands out in multiple avenues as follows. It resolves ambiguities well, and maintains consistency in object placement. Moreover, it adapts to diverse task-based classifications. Furthermore, it contributes to explainable AI, hence helping to improve trust and human-robot collaboration. Controlled experiments performed in our work, simulating domestic robotics settings, make Robo-CSK-Organizer demonstrate superior performance while placing objects in contextually relevant locations. This work highlights the capacity of an AI-based system to conduct commonsense-guided decision-making in robotics closer to the thresholds of human cognition. Hence, Robo-CSK-Organizer makes positive impacts on AI and robotics. |
| title | Robo-CSK-Organizer: Commonsense Knowledge to Organize Detected Objects for Multipurpose Robots |
| topic | Robotics Artificial Intelligence I.2.6; I.2.9 |
| url | https://arxiv.org/abs/2409.18385 |