Author: commandia

Title: Prediction of tactile perception from vision on deformable objects

Authors: Brayan S. Zapata-Impata and Pablo Gil

Workshop: Robotic Manipulation of Deformable Objects (ROMADO), 25 October – 25 December, 2020

Abstract: Through the use of tactile perception, a manipulator can estimate the stability of its grip, among others. However, tactile sensors are only activated upon contact. In contrast, humans can estimate the feeling of touching an object from its visual appearance. Providing robots with this ability to generate tactile perception from vision is desirable to achieve autonomy. To accomplish this, we propose using a Generative Adversarial Network. Our system learns to generate tactile responses using as stimulus a visual representation of the object and target grasping data. Since collecting labeled samples of robotic tactile responses consumes hardware resources and time, we apply semi-supervised techniques. For this work, we collected 4000 samples with 4 deformable items and experiment with 4 tactile modalities.

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Title: Simultaneous shape control and transport with multiple robots

Author: G. López-Nicolás, R. Herguedas, M. Aranda, Y. Mezouar.

Journal: IEEE International Conference on Robotic Computing (IRC), pp. 218-225, 2020.

Abstract: Autonomous transport of objects may require multiple robots when the object is large or heavy. Besides, in the case of deformable objects, a set of robots may also be needed to maintain or adapt the shape of the object to the task requirements. The task we address consists in transporting an object, represented as a two dimensional shape or contour, along a desired path. Simultaneously, the team of robots grasping the object is controlled to the desired contour points configuration. Since the mobile robots of the team obey nonholonomic motion constraints, admissible trajectories are designed to keep the integrity of the object while following the prescribed path. Additionally, the simultaneous control of the object’s shape is smoothly performed to respect the admissible deformation of the object. The main contribution lies in the definition of the grasping robots’ trajectories dealing with the involved constraints. Different simulations, where the deformable object dynamics are modelled with consensus-based techniques, illustrate the performance of the approach.

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Title: Distributed relative localization using the multi-dimensional weighted centroid
Author: R. Aragüés, A. González, G. López-Nicolás, C. Sagüés.
Journal: IEEE Transactions on Control of Network Systems, vol. 7, pp. 1272-1282, 2020.

Abstract: A key problem in multi-agent systems is the distributed estimation of the localization of agents in a common reference from relative measurements. Estimations can be referred to an anchor node or, as we do here, referred to the weighted centroid of the multi-agent system. We propose a Jacobi Over–Relaxation method for distributed estimation of the weighted centroid of the multi-agent system from noisy relative measurements. Contrary to previous approaches, we consider relative multi-dimensional measurements with general covariance matrices not necessarily fully diagonal. We analyze the method convergence and provide mathematical constraints that ensure avoiding ringing phenomena. We also prove our weighted centroid method converges faster than anchor-based solutions.
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Title: Dynamic occlusion handling for real time object perception

Authors: Ignacio Cuiral-Zueco and Gonzalo Lopez-Nicolas

Conference: International Conference on Robotics and Automation Engineering

(ICRAE 2020), November 20-22, 2020

Abstract: An RGB-D based occlusion-handling camera position computation method for proper object perception has been designed and implemented. This proposal is an improved alternative to our previous optimisation-based approach where the contribution is twofold: this new method is geometric-based and it is also able to handle dynamic occlusions. This approach makes extensive use of a ray-projection model where a key aspect is that the solution space is defined within a sphere surface around the object. The method has been designed with a view to robotic applications and therefore provides robust and versatile features. Therefore, it does not require training nor prior knowledge of the scene, making it suitable for diverse applications and scenarios. Satisfactory results have been obtained with real time experiments.

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