8 research outputs found
Interactive Perception for Cluttered Environments
Robotics research tends to focus upon either non-contact sensing or machine manipulation, but not both. This paper explores the benefits of combining the two by addressing the problem of extracting and classifying unknown objects within a cluttered environment, such as found in recycling and service robot applications. In the proposed approach, a pile of objects lies on a flat background, and the goal of the robot is to sift through the pile and classify each object so that it can be studied further. One object should be removed at a time with minimal disturbance to the other objects. We propose an algorithm, based upon graph-based segmentation and stereo matching, that automatically computes a desired grasp point that enables the objects to be removed one at a time. The algorithm then isolates each object to be classified by color, shape and flexibility. Experiments on a number of different objects demonstrate the ability of classifying each item through interaction and labeling them for further use and study
Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics
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A Survey of Knowledge Representation in Service Robotics
Within the realm of service robotics, researchers have placed a great amount
of effort into learning, understanding, and representing motions as
manipulations for task execution by robots. The task of robot learning and
problem-solving is very broad, as it integrates a variety of tasks such as
object detection, activity recognition, task/motion planning, localization,
knowledge representation and retrieval, and the intertwining of
perception/vision and machine learning techniques. In this paper, we solely
focus on knowledge representations and notably how knowledge is typically
gathered, represented, and reproduced to solve problems as done by researchers
in the past decades. In accordance with the definition of knowledge
representations, we discuss the key distinction between such representations
and useful learning models that have extensively been introduced and studied in
recent years, such as machine learning, deep learning, probabilistic modelling,
and semantic graphical structures. Along with an overview of such tools, we
discuss the problems which have existed in robot learning and how they have
been built and used as solutions, technologies or developments (if any) which
have contributed to solving them. Finally, we discuss key principles that
should be considered when designing an effective knowledge representation.Comment: Accepted for RAS Special Issue on Semantic Policy and Action
Representations for Autonomous Robots - 22 Page
Alternative Object Use in Adults and Children: Embodied Cognitive Bases of Creativity
Why does one need creativity? On a personal level, improvisation with available resources is needed for online coping with unforeseen environmental stimuli when existing knowledge and apparent action strategies do not work. On a cultural level, the exploitation of existing cultural means and norms for the deliberate production of novel and valuable artifacts is a basis for cultural and technological development and extension of human action possibilities across various domains. It is less clear, however, how creativity develops and how exactly one arrives at generating new action possibilities and producing multiple alternative action strategies using familiar objects. In this theoretical paper, we first consider existing accounts of the creative process in the Alternative Uses Task and then present an alternative interpretation, drawing on sociocultural views and an embodied cognition approach. We explore similarities between the psychological processes underlying the generation of new uses in the Alternative Uses Task and children’s pretend play. We discuss possible cognitive mechanisms and speculate how the generation of new action possibilities for common objects in pretend play can be related to adults’ ability to generate new action strategies associated with object use. Implications for creativity development in humans and embodied artificial agents are discussed