Luka Lukic

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Efficient, adaptive and reliable visuomotor control system is crucial to enable robots to display flexibility in the face of changes in the environment. This paper takes inspiration in human eye-arm-hand coordination pattern to develop an equivalently robust robot controller. We recorded gaze, arm, hand, and trunk data from human subjects in reaching and(More)
We investigate the role of obstacle avoidance in visually guided reaching and grasping movements. We report on a human study in which subjects performed prehensile motion with obstacle avoidance where the position of the obstacle was systematically varied across trials. These experiments suggest that reaching with obstacle avoidance is organized in a(More)
This paper presents a novel, biologically-inspired, approach for an efficient management of computational resources for visual processing. In particular, we modulate a visual “attentional landscape” with the motor plans of a robot. The attentional landscape is a more recent, general and a more complex concept of an arrangement of spatial attention than a(More)
We present a novel, biologically-inspired, approach to an efficient allocation of visual resources for humanoid robots in a form of a motor-primed visual attentional landscape. The attentional landscape is a more general, dynamic and a more complex concept of an arrangement of spatial attention than the popular “attentional spotlight” or “zoom-lens” models(More)
Two reference membrane filtration methods (Standard Methods: SM 9213E and U.S.EPA), the Most Probable Number method (Pseudalert®) and a membrane filtration method currently used by the Ontario Ministry of the Environment and Climate Change (MOECC) Laboratory Services Branch Etobicoke, Canada (Method E3371) were compared for the detection and recovery of(More)
U nderstanding the principles involved in visually-based coordinated motor control is one of the most fundamental and most intriguing research problems across a number of areas, including psychology, neuroscience, computer vision and robotics. Humans perform visually driven actions such looking at, reaching, and grasping a morning cup of co ee on a daily(More)
Abstract. The vast streams of data created by camera networks render unfeasible browsing all data, relying only on human resources. Automation is required for detecting and tracking multiple targets by using multiple cooperating cameras. In order to effectively track multiple targets, autonomous active camera networks require adequate scheduling and control(More)
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