Javier Felip

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We consider the problem of grasp and manipulation planning when the state of the world is only partially observable. Specifically, we address the task of picking up unknown objects from a table top. The proposed approach to object shape prediction aims at closing the knowledge gaps in the robot's understanding of the world. A completed state estimate of the(More)
This paper addresses the problem of robot grasping in conditions of uncertainty. We propose a grasp controller that deals robustly with this uncertainty using feedback from different contact-based sensors. This controller assumes a description of grasp consisting of a primitive that only determines the initial configuration of the hand and the control law(More)
Robot perception of physical interaction with the world can be achieved based on different sensory modalities: tactile, force-torque, vision, laser, sonar, proprioception, accelerometers, etc. An important problem and research topic in robotics is the question of how to fuse multiple sensory modalities to provide the robot with advanced perception(More)
The adoption of robots for service tasks in natural environments calls for the use of sensors to allow manipulation of objects under imperfect environment knowledge and the use of knowledge transfer from humans. This paper addresses these challenges by proposing a new abstraction architecture for embodiment independent sensor-based control of manipulation.(More)
In this work, we address the problem of detecting contacts between a robot hand and an object during the approach and execution phases of manipulation tasks in the absence of touch perception. In order to detect contact in such conditions, we implemented a method which uses the visual tracking of objects using ICP (Iterative Closest Point) to detect small(More)