Search results for "robotics"
showing 10 items of 484 documents
Bio-Inspired Polarization Vision Techniques for Robotics Applications
2015
Researchers have been inspired by nature to build the next generation of smart robots. Based on the mechanisms adopted by the animal kingdom, research teams have developed solutions to common problems that autonomous robots faced while performing basic tasks. Polarization-based behaviour is one of the most distinctive features of some species of the animal kingdom. Light polarization parameters significantly expand visual capabilities of autonomous robots. Polarization vision can be used for most tasks of color vision, like object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. In this chapter, the authors briefly cover polarization-based vis…
An Application of Iterative Identification and Control in the Robotics Field
2006
The plant model appropriate for designing the control strongly depends on the requirements. Simple models are enough to compute nondemanding controls. The parameters of well-defined structural models of flexible robot manipulators are difficult to determine because their effect is only visible if the manipulator is under strong actions or with high-frequency excitation. Thus, in this chapter, an iterative approach is suggested. This approach is applied to a one-degree-of-freedom flexible robot manipulator, first using some well-known models and then controlling a lab prototype. This approach can be used with a variety of control design and/or identification techniques.
The role of synergies within generative models of action execution and recognition: A computational perspective
2015
Controlling the body – given its huge number of degrees of freedom – poses severe computational challenges. Mounting evidence suggests that the brain alleviates this problem by exploiting “synergies”, or patterns of muscle activities (and/or movement dynamics and kinematics) that can be combined to control action, rather than controlling individual muscles of joints [1–10]. D’Ausilio et al. [11] explain how this view of motor organization based on synergies can profoundly change the way we interpret studies of action recognition in humans and monkeys, and in particular the controversy on the “granularity” of the mirror neuron system (MNs): whether it encodes either (lower) kinematic aspects…
Automatic place detection and localization in autonomous robotics
2007
This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as …
Multimodal 2D Image to 3D Model Registration via a Mutual Alignment of Sparse and Dense Visual Features
2018
International audience; Many fields of application could benefit from an accurate registration of measurements of different modalities over a known 3D model. However, aligning a 2D image to a 3D model is a challenging task and is even more complex when the two have a different modality. Most of the 2D/3D registration methods are based on either geometric or dense visual features. Both have their own advantages and their own drawbacks. We propose, in this paper, to mutually exploit the advantages of one feature type to reduce the drawbacks of the other one. For this, an hybrid registration framework has been designed to mutually align geometrical and dense visual features in order to obtain …
Evaluating State-Based Intention Recognition Algorithms against Human Performance
2014
In this paper, we describe a novel intention recognition approach based on the representation of state information in a cooperative human-robot environment. We compare the output of the intention recognition algorithms to those of an experiment involving humans attempting to recognize the same intentions in a manufacturing kitting domain. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the approaches described in this paper to infer the likelihood of subsequent actions occurring. This wo…
Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems
2017
A mechanism of coalition formation in the metaphor of politics multiagent architecture
2003
Hybrid Multi-Agent Architectures allow the support of mobile robots colonies moving in dynamic, not predictable and time variable environments in order to achieve distributed solving strategies that develop collective team-oriented behaviors for solving complicate and difficult tasks. The development of a new robotic architecture for the coordination of a robot colonies in dangerous, unknown and dynamic environment is outlined. The name of this new architecture is Metaphor of Politics (MP), because it loosely takes inspiration from the political organizations of democratic governments.
A Cognitive Framework for Imitation Learning
2006
Abstract In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how this Conceptual Area can be employed to efficiently organize perceptual data, to learn movement primitives from human demonstration and to generate complex actions by combining and sequencing simpler ones. The proposed architecture ha…
ACCURATE DENSE STEREO MATCHING FOR ROAD SCENES
2017
International audience; Stereo matching task is the core of applications linked to the intelligent vehicles. In this paper, we present a new variant function of the Census Transform (CT) which is more robust against radiometric changes in real road scenes. We demonstrate that the proposed cost function outperforms the conventional cost functions using the KITTI benchmark. The cost aggregation method is also updated for taking into account the edge information. This enables to improve significantly the aggregated costs especially within homogenous regions. The Winner-Takes-All (WTA) strategy is used to compute disparity values. To further eliminate the remainder matching ambiguities , a post…