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相关论文: A Personalized Household Assistive Robot that Lear…

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Assistive robots operating in household environments would require items to be available in the house to perform assistive tasks. However, when these items run out, the assistive robot must remind its user to buy the missing items. In this…

机器人学 · 计算机科学 2022-07-21 Ali Ayub , Chrystopher L. Nehaniv , Kerstin Dautenhahn

Wheelchair-mounted robotic arms (and other assistive robots) should help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control…

机器人学 · 计算机科学 2021-09-29 Ananth Jonnavittula , Dylan P. Losey

For robots to perform assistive tasks in unstructured home environments, they must learn and reason on the semantic knowledge of the environments. Despite a resurgence in the development of semantic reasoning architectures, these methods…

机器人学 · 计算机科学 2024-03-07 Ali Ayub , Chrystopher Nehaniv , Kerstin Dautenhahn

The ability to recognize human partners is an important social skill to build personalized and long-term human-robot interactions, especially in scenarios like education, care-giving, and rehabilitation. Faces and voices constitute two…

It is intractable for assistive robots to have all functionalities pre-programmed prior to deployment. Rather, it is more realistic for robots to perform supplemental, on-site learning about user's needs and preferences, and particularities…

机器人学 · 计算机科学 2022-10-19 Nina Moorman , Erin Hedlund-Botti , Matthew Gombolay

In an efficient and flexible human-robot collaborative work environment, a robot team member must be able to recognize both explicit requests and implied actions from human users. Identifying "what to do" in such cases requires an agent to…

机器人学 · 计算机科学 2023-09-25 Syed T. Bukhari , Bashira Akter Anima , David Feil-Seifer , Wajahat M. Qazi

It is important for socially assistive robots to be able to recognize when a user needs and wants help. Such robots need to be able to recognize human needs in a real-time manner so that they can provide timely assistance. We propose an…

机器人学 · 计算机科学 2021-10-22 Jason R. Wilson , Phyo Thuta Aung , Isabelle Boucher

Assistive robot arms can help humans by partially automating their desired tasks. Consider an adult with motor impairments controlling an assistive robot arm to eat dinner. The robot can reduce the number of human inputs -- and how precise…

机器人学 · 计算机科学 2024-03-19 Joshua Hoegerman , Shahabedin Sagheb , Benjamin A. Christie , Dylan P. Losey

Assistive robot arms try to help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control over the robot's motion: as the robot…

机器人学 · 计算机科学 2024-02-19 Ananth Jonnavittula , Shaunak A. Mehta , Dylan P. Losey

In this paper, we propose a concept learning architecture that enables a robot to build symbols through self-exploration by interacting with a varying number of objects. Our aim is to allow a robot to learn concepts without constraints,…

机器人学 · 计算机科学 2024-01-03 Alper Ahmetoglu , Erhan Oztop , Emre Ugur

Assistive robots enable people with disabilities to conduct everyday tasks on their own. However, these tasks can be complex, containing both coarse reaching motions and fine-grained manipulation. For example, when eating, not only does one…

机器人学 · 计算机科学 2020-05-12 Hong Jun Jeon , Dylan P. Losey , Dorsa Sadigh

Developing robots that can assist humans efficiently, safely, and adaptively is crucial for real-world applications such as healthcare. While previous work often assumes a centralized system for co-optimizing human-robot interactions, we…

机器人学 · 计算机科学 2024-12-30 Jason Qin , Shikun Ban , Wentao Zhu , Yizhou Wang , Dimitris Samaras

Home robots may come with many sophisticated built-in abilities, however there will always be a degree of customization needed for each user and environment. Ideally this should be accomplished through one-shot learning, as collecting the…

人工智能 · 计算机科学 2019-11-25 Jonathan Connell

To be capable of lifelong learning in a real-life environment, robots have to tackle multiple challenges. Being able to relate physical properties they may observe in their environment to possible interactions they may have is one of them.…

人工智能 · 计算机科学 2020-09-24 Alexandre Manoury , Sao Mai Nguyen , Cédric Buche

We consider the problem of building an assistive robotic system that can help humans in daily household cleanup tasks. Creating such an autonomous system in real-world environments is inherently quite challenging, as a general solution may…

The Memory-Centred Cognition perspective places an active association substrate at the heart of cognition, rather than as a passive adjunct. Consequently, it places prediction and priming on the basis of prior experience to be inherent and…

机器人学 · 计算机科学 2016-02-19 Paul Baxter

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The…

The topic of joint actions has been deeply studied in the context of Human-Human interaction in order to understand how humans cooperate. Creating autonomous robots that collaborate with humans is a complex problem, where it is relevant to…

机器人学 · 计算机科学 2016-03-03 Sandra Devin , Grégoire Milliez , Michelangelo Fiore , Aurélie Clodic , Rachid Alami

This paper presents a hybrid robot cognitive architecture, CRAM, that enables robot agents to accomplish everyday manipulation tasks. It addresses five key challenges that arise when carrying out everyday activities. These include (i) the…

机器人学 · 计算机科学 2023-04-28 Michael Beetz , Gayane Kazhoyan , David Vernon

With the introduction of collaborative robots, humans and robots can now work together in close proximity and share the same workspace. However, this collaboration presents various challenges that need to be addressed to ensure seamless…

机器人学 · 计算机科学 2023-07-24 Ali Noormohammadi-Asl , Ali Ayub , Stephen L. Smith , Kerstin Dautenhahn
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