Quick Search:

uzh logo
Browse by:

Zurich Open Repository and Archive

Maintenance: Tuesday, July the 26th 2016, 07:00-10:00

ZORA's new graphical user interface will be relaunched (For further infos watch out slideshow ZORA: Neues Look & Feel). There will be short interrupts on ZORA Service between 07:00am and 10:00 am. Please be patient.

Hoffmann, Matej; Oses, Noelia; Koene, Randal A (2010). Embodied moving-target seeking with prediction and planning. Lecture Notes in Computer Science, 6077:478-485.

Full text not available from this repository.

View at publisher


We present a bio-inspired control method for moving-target seeking with a mobile robot, which resembles a predator-prey scenario. The motor repertoire of a simulated Khepera robot was restricted to a discrete number of "gaits". After an exploration phase, the robot automatically synthesizes a model of its motor repertoire, acquiring a forward model. Two additional components were introduced for the task of catching a prey robot. First, an inverse model to the forward model, which is used to determine the action (gait) needed to reach a desired location. Second, while hunting the prey, a model of the prey's behavior is learned online by the hunter robot. All the models are learned ab initio, without assumptions, work in egocentric coordinates, and are probabilistic in nature. Our architecture can be applied to robots with any physical constraints (or embodiment), such as legged robots.



Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Date:25 June 2010
Deposited On:12 Feb 2011 08:24
Last Modified:05 Apr 2016 14:35
Publisher DOI:10.1007/978-3-642-13803-4_59

Users (please log in): suggest update or correction for this item

Repository Staff Only: item control page