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Experimental Comparison of Uncertainty Criteria for Active SLAM

Experimental Comparison of Uncertainty Criteria for Active SLAM. Henry Carrillo. Motivación. Preliminares. Experimentos. Primer experimento : acerca del calculo Segundo experimento : SLAM activo. Robot simulado ambiente interior : MRPT / C++

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Experimental Comparison of Uncertainty Criteria for Active SLAM

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  1. Experimental Comparison of Uncertainty Criteria forActive SLAM Henry Carrillo

  2. Motivación

  3. Preliminares

  4. Experimentos • Primer experimento : acerca del calculo • Segundo experimento : SLAM activo • Robot simulado ambiente interior : MRPT / C++ • Robot real ambiente interior : Pioneer 3 DX - ad-hoc • Robot real ambiente interior : DLR dataset • Robot real ambiente exterior : Victoria Park dataset • Robot simulado con horizonte unitario : MRPT / C++

  5. Primer experimento • Primer experimento : acerca del calculo • Es posible calcular D-opt en un robot realizando SLAM? • Ejecutamos un algoritmo de SLAM "secuencial" (e.g EKF-SLAM, iSAM) • Calculamos en cada paso : A-opt, E-opt , D-opt, det. de la covarianza, entropía e información mutua. • Robot simulado ambiente interior : MRPT / C++ • Robot real ambiente interior : Pioneer 3 DX - ad-hoc • Robot real ambiente interior : DLR dataset • Robot real ambiente exterior : Victoria Park dataset

  6. 1E - Robot simulado ambiente interior (I) Escenario: • Área de 25x25m • 2D EKF-SLAM • Sensor: Odometria+cámara(360 - 3m rango) • 180 landmarks - DA conocida • Errores Gaussianos: • Odometria + sensores

  7. 1E - Robot simulado ambiente interior (II) (a)-(f) A-opt, E-opt, D-opt, determinant, entropy and MI

  8. 1E-Robot en ambiente interior @ DLR (I) Escenario: • Oficina 60x40 m • 2D EKF-SLAM • Sensor: • Odometria + cámara BW • 576 landmarks– DA conocida

  9. 1E-Robot en ambiente interior @ DLR (II) (a)-(f) A-opt, E-opt, D-opt, determinant, entropy and MI

  10. 1E-Robot en ambiente exterior @ VP (I) Escenario: • Parque de 350 x 350 m • iSAM • Sensor: Odometria + Laser • xxx landmarks– DA conocida

  11. 1E-Robot en ambiente exterior @ VP (II) (a)-(f) A-opt, E-opt, D-opt, determinant, entropy and MI

  12. 1E-Robot en ambiente interior ad-hoc (I) Escenario: • Área de 25x25m • 2D EKF-SLAM • Sensor: Odometria+cámara • (360 - 3m rango) • 180 landmarks - DA conocida • Errores Gaussianos: • Odometria + sensores

  13. 1E-Robot en ambiente interior ad-hoc (II) (a)-(f) A-opt, E-opt, D-opt, determinant, entropy and MI

  14. Segundo experimento • Segundo experimento : SLAM activo • Que efecto tiene la métrica de incertidumbre en el SLAM activo? • SLAM activo == Horizonte unitario (greedy), discreto. • Métricas de incertidumbre == A-opt, D-opt y entropía. • Efecto == MSE y • Robot simulado con horizonte unitario : MRPT / C++

  15. 2E-Robot en ambiente interior ad-hoc (I) Escenario: • Área de 20x20m y 30x30m • 2D EKF-SLAM • Sensor: Odometria+cámara(360 - 3m rango) • Errores Gaussianos: Odometria+sensores • Planeador de caminos: Discreto (A*) y continuo (Atraccion-Repulsion)

  16. 2E-Robot en ambiente interior ad-hoc (II) • Resulting paths from each uncertainty metric: (a) D-opt, (b) A-opt and (c) Entropy. Each colour represents an executed path. The planning area was 20 x 20 m.

  17. 2E-Robot en ambiente interior ad-hoc (III) • Resulting trajectories for a 10000 steps active SLAM simulation. (a). Predefined trajectory and landmarks ground truth. (b). A-opt based active SLAM. (c). D-opt based active SLAM.

  18. 2E - Análisis cuantitativo 30x30 m • Evolution of the MSE ((a)-(c)) and 2 ((d)-(f)). Average of 10 MC.

  19. 2E - Análisis cuantitativo 20x20 m • Evolution of the MSE ((a)-(c)) and 2 ((d)-(f)). Average of 10 MC.

  20. Take home message

  21. Experimental Comparison of UncertaintyCriteriafor Active SLAM Gracias!!!

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