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Nombre de programmes trouvés : 2817

Label UNT Vidéocours

le 01/06/2015 (7m22s)

3.6. Observability in robotics

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.

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Label UNT Vidéocours

le 01/06/2015 (6m57s)

3.7. Observability Rank Criterion

In this video, we discuss an automatic method which is analytical and allows us to answer the question if a state is observable or not: this method is the Observability Rank Criterion which has been introduced by Herman Krener in 1977.

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Label UNT Vidéocours

le 01/06/2015 (7m42s)

4.2. Dynamic Probabilistic Grids – Bayesian Occupancy Filter concept

This video will show how to describe Bayesian occupancy filter concept.

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Label UNT Vidéocours

le 01/06/2015 (6m14s)

4.3. Dynamic Probabilistic Grids – Implementation approaches

This video addresses the problem of the practical implementation for the dynamic probabilistic grid.

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Label UNT Vidéocours

le 01/06/2015 (7m40s)

4.1. Robot Perception for Dynamic environments: Outline & DP-Grids concept

The fourth part of the course addresses perception, situation awareness and decision making. In this first video, we're giving an outline of the problem and introducing the new concept of dynamic probability grids.

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Label UNT Vidéocours

le 01/06/2015 (6m13s)

4.4. Object level Perception functions (SLAM + DATMO)

This video is dedicated to the object level perception functions: Simultaneous Localization Mapping (SLAM) and Detection and Tracking surrounding Mobile Objects (DATMO).

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Label UNT Vidéocours

le 01/06/2015 (6m47s)

4.5. Detection and Tracking of Mobile Objects – Problem & Approaches

This video adresses the Detection and Tracking of Mobile Objects (DATMO) problem.

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Label UNT Vidéocours

le 01/06/2015 (6m16s)

4.6. Detection and Tracking of Mobile Objects – Model & Grid based approaches

This video addresses the question of model-based and grid-based approaches.

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Label UNT Vidéocours

le 01/06/2015 (6m37s)

4.7. Embedded Bayesian Perception & Short-term collision risk (DP-Grid level)

This video deals with embedded Bayesian perception and short-term collision risk.

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Label UNT Vidéocours

le 01/06/2015 (9m45s)

4.9. Situation Awareness – Collision Risk Assessment & Decision (Object level)

This video addresses the problem of collision risk assessment and decision.

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