The PlayMate System

Hawes, Nick; Wyatt, Jeremy C; Sridharan, Mohan; Kopicki, Marek; Hongeng, Somboon; Calvert, I. A.; Sloman, Aaron; Kruijff, Geert-Jan M.; Jacobsson, Henrik; Brenner, Michael; Skočaj, Danijel; Vrečko, Alen; Majer, Nikodem; Zillich, Michael

doi:10.1007/978-3-642-11694-0_9

Cited by 5 publications

(3 citation statements)

References 5 publications

(3 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interactive approaches require that the robot asks the human to provide input if it encounters a problem. For example, systems have been developed which ask a human whether it has just passed a door [2], and which use uncertain categorisations as the basis for dialogue about room categories [1] and object features [7].…”

Section: Background and Related Workmentioning

confidence: 99%

Home alone: Autonomous extension and correction of spatial representations

Hawes

Hanheide

Hargreaves

et al. 2011

2011 IEEE International Conference on Robotics and Automation

Self Cite

View full text Add to dashboard Buy / Rent full text

Abstract-In this paper we present an account of the problems faced by a mobile robot given an incomplete tour of an unknown environment, and introduce a collection of techniques which can generate successful behaviour even in the presence of such problems. Underlying our approach is the principle that an autonomous system must be motivated to act to gather new knowledge, and to validate and correct existing knowledge. This principle is embodied in Dora, a mobile robot which features the aforementioned techniques: shared representations, non-monotonic reasoning, and goal generation and management. To demonstrate how well this collection of techniques work in real-world situations we present a comprehensive analysis of the Dora system's performance over multiple tours in an indoor environment. In this analysis Dora successfully completed 18 of 21 attempted runs, with all but 3 of these successes requiring one or more of the integrated techniques to recover from problems.

show abstract

Section: Background and Related Workmentioning

confidence: 99%

Home alone: Autonomous extension and correction of spatial representations

Hawes

Hanheide

Hargreaves

et al. 2011

2011 IEEE International Conference on Robotics and Automation

Self Cite

View full text Add to dashboard Buy / Rent full text

show abstract

“…It is necessary to focus more on creating complete, integrated systems that sense and interact with their surroundings, rather than looking at just subsets of the problem in isolation. The DARPA initiatives [21,56,22], the EU Cognitive Systems (CoSy) project [43], and the RoboCup initiative [51] are all excellent examples of tasks that aim to create such integrated systems. These initiatives force the researchers to identify and tackle key problems that would not arise in the absence of such practical challenges.…”

Section: Summary and Future Workmentioning

confidence: 99%

“…The robot would need capabilities such as spatial and semantic reasoning [55], analysis of 3D geometric structure, and natural language processing during human-robot interactions [54]. As the focus shifts towards developing such "cognitive" abilities on a mobile robot, including the ability to reason and bind information across different sensing modalities, it becomes necessary to design architectures that enable autonomous learning and adaptation in complex systems [43]. Ultimately, the goal is to enable widespread mobile robot deployment in a range of applications, with the robots operating autonomously and interacting with humans under completely uncontrolled natural conditions.…”

Section: Summary and Future Workmentioning

confidence: 99%

Color learning and illumination invariance on mobile robots: A survey

Sridharan

Stone

2009

Robotics and Autonomous Systems

Self Cite

View full text Add to dashboard Buy / Rent full text

Recent developments in sensor technology have made it feasible to use mobile robots in several fields, but robots still lack the ability to accurately sense the environment. A major challenge to the widespread deployment of mobile robots is the ability to function autonomously, learning useful models of environmental features, recognizing environmental changes, and adapting the learned models in response to such changes. This article focuses on such learning and adaptation in the context of color segmentation on mobile robots in the presence of illumination changes. The main contribution of this article is a survey of vision algorithms that are potentially applicable to color-based mobile robot vision. We therefore look at algorithms for color segmentation, color learning and illumination invariance on mobile robot platforms, including approaches that tackle just the underlying vision problems. Furthermore, we investigate how the interdependencies between these modules and high-level action planning can be exploited to achieve autonomous learning and adaptation. The goal is to determine the suitability of the state-of-the-art vision algorithms for mobile robot domains, and to identify the challenges that still need to be addressed to enable mobile robots to learn and adapt models for color, so as to operate autonomously in natural conditions.

show abstract

The PlayMate System

Cited by 5 publications

References 5 publications

Home alone: Autonomous extension and correction of spatial representations

Home alone: Autonomous extension and correction of spatial representations

Color learning and illumination invariance on mobile robots: A survey

Contact Info

Product

Resources

About