Living and Searching in the World: Object-Based State Estimation for Mobile Robots

التفاصيل البيبلوغرافية
العنوان: Living and Searching in the World: Object-Based State Estimation for Mobile Robots
المؤلفون: Lawson Wong
المصدر: Proceedings of the AAAI Conference on Artificial Intelligence. 28
بيانات النشر: Association for the Advancement of Artificial Intelligence (AAAI), 2014.
سنة النشر: 2014
مصطلحات موضوعية: General Medicine
الوصف: Mobile-manipulation robots performing service tasks in human-centric indoor environments has long been a dream for developers of autonomous agents. Tasks such as cooking and cleaning require interaction with the environment, hence robots need to know relevant aspects of their spatial surroundings. However, unlike the structured settings that industrial robots operate in, service robots typically have little prior information about their environment. Even if this information was given, due to the involvement of many other agents (e.g., humans moving objects), uncertainty in the complete state of the world is inevitable over time. Additionally, most information about the world is irrelevant to any particular task at hand. Mobile manipulation robots therefore need to continuously perform the task of state estimation, using perceptual information to maintain the state, and its uncertainty, of task-relevant aspects of the world. Because indoor tasks frequently require the use of objects, objects should be given critical emphasis in spatial representations for service robots. Compared to occupancy grids and feature-based maps often used in navigation and SLAM, object-based representations are arguably still in their infancy. In my thesis, I propose a representation framework based on objects, their 'semantic' attributes, and their geometric realizations in the physical world.
تدمد: 2374-3468
2159-5399
DOI: 10.1609/aaai.v28i1.8785
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::91d64a0d17d12fdf8a3e63ef84921081
https://doi.org/10.1609/aaai.v28i1.8785
رقم الانضمام: edsair.doi...........91d64a0d17d12fdf8a3e63ef84921081
قاعدة البيانات: OpenAIRE
الوصف
تدمد:23743468
21595399
DOI:10.1609/aaai.v28i1.8785