Control of Redundant Joint Structures Using Image Information During the Tracking of Non-Smooth Trajectories

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Title: Control of Redundant Joint Structures Using Image Information During the Tracking of Non-Smooth Trajectories
Authors: Lorenzo, Gonzalo | Pomares, Jorge | Lledó Carreres, Asunción | Jara, Carlos A.
Research Group/s: EDUTIC- ADEI (Educación y Tecnologías de la Información y Comunicación- Atención a la Diversidad. Escuela Inclusiva) | Automática, Robótica y Visión Artificial
Center, Department or Service: Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Departamento de Psicología Evolutiva y Didáctica
Keywords: Service robots | Robot vision | Image-based control | Control of joint structures
Knowledge Area: Ingeniería de Sistemas y Automática | Didáctica y Organización Escolar
Issue Date: 17-Jun-2014
Publisher: Springer Science+Business Media Dordrecht
Citation: Journal of Intelligent & Robotic Systems. 2014, June. doi:10.1007/s10846-014-0069-y
Abstract: Visual information is increasingly being used in a great number of applications in order to perform the guidance of joint structures. This paper proposes an image-based controller which allows the joint structure guidance when its number of degrees of freedom is greater than the required for the developed task. In this case, the controller solves the redundancy combining two different tasks: the primary task allows the correct guidance using image information, and the secondary task determines the most adequate joint structure posture solving the possible joint redundancy regarding the performed task in the image space. The method proposed to guide the joint structure also employs a smoothing Kalman filter not only to determine the moment when abrupt changes occur in the tracked trajectory, but also to estimate and compensate these changes using the proposed filter. Furthermore, a direct visual control approach is proposed which integrates the visual information provided by this smoothing Kalman filter. This last aspect permits the correct tracking when noisy measurements are obtained. All the contributions are integrated in an application which requires the tracking of the faces of Asperger children.
ISSN: 0921-0296 (Print) | 1573-0409 (Online)
DOI: 10.1007/s10846-014-0069-y
Language: eng
Type: info:eu-repo/semantics/article
Rights: The final publication is available at Springer via
Peer Review: si
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