1.3. New challenges for Robotics in Human Environments
Introducing robots in human environments bring new challenges to robotics.
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Introducing robots in human environments bring new challenges to robotics.
In this video, we are discussing the SLAM problem: simultaneous localization and mapping.
In this video we are aiming to improve on the results we obtained in video 5.3a, in particular with respect to the greyed-out trajectories that are badly represented.
Accessible à de nombreuses applications, tant en biologie ou qu'en technologie des pêches, la vidéo sous-marine est de plus en plus utilisée dans le domaine de la recherche halieutique. Les progrès
This video addresses sensing technologies. Sensing technologies is one of the key functions for autonomous robots. Sensing is performed using various internal and external sensors.
In this video we want to apply the observability rank criterion to understand the observability properties of the system that we saw in the previous videos.
In this video we will review the base filter and we will study a particular instance of the Bayesian filter called Hidden Markov models which is a discrete version of a Bayesian filter.
L’évolution des technologies d’observation et de modélisation a joué un rôle central dans l’accroissement des connaissances sur le fonctionnement des océans ou dans le développement des activités
This video addresses sensing technology, and focuses on robot control and human-robot interaction applications.
In this video we discuss a fundamental issue which arises when we deal with an estimation problem: understanding if the system contains enough information to perform the estimation of the state.
In this video we are going to apply the concepts we have reviewed in the video 5.4 into real trajectories.
This video presents the basic technologies for navigation in dynamic human environments. The objective is to achieve goal oriented navigation in open, dynamic and uncertain environments populated