license: mit
task_categories:
- robotics
language:
- en
tags:
- AI
- ICRA
ICRA 2024 Accepted Paper Meta Info Dataset
This dataset is collect from the ICRA 2024 IEEE International Conference on Robotics and Automation (ICRA) 2024 accepted papers' meta info (https://ieeexplore.ieee.org/xpl/conhome/10609961/proceeding) as well as the arxiv website DeepNLP paper arxiv (http://www.deepnlp.org/content/paper/icra2024). For researchers who are interested in doing analysis of ICRA 2024 accepted papers and potential trends, you can use the already cleaned up json files. Each row contains the meta information of a paper in the ICRA 2024 conference. To explore more AI & Robotic papers (NIPS/ICML/ICLR/IROS/ICRA/etc) and AI equations, feel free to navigate the Equation Search Engine (http://www.deepnlp.org/search/equation) as well as the AI Agent Search Engine to find the deployed AI Apps and Agents (http://www.deepnlp.org/search/agent) in your domain.
Equations Latex code and Papers Search Engine
Meta Information of Json File of Paper
{
"title": "TinyMPC: Model-Predictive Control on Resource-Constrained Microcontrollers",
"detail_url": "https://ieeexplore.ieee.org/document/10610987/",
"author_list": ["Khai Nguyen", "Sam Schoedel", "Anoushka Alavilli", "Brian Plancher", "Zachary Manchester", "Khai Nguyen", "Sam Schoedel", "Anoushka Alavilli", "Brian Plancher", "Zachary Manchester"],
"abstract": "Model-predictive control (MPC) is a powerful tool for controlling highly dynamic robotic systems subject to complex constraints. However, MPC is computationally demanding, and is often impractical to implement on small, resource-constrained robotic platforms. We present TinyMPC, a high-speed MPC solver with a low memory footprint targeting the microcontrollers common on small robots. Our approach ..."
}
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