Virtual Testbeds for Planetary Exploration: The Self Localization Aspect

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1 Virtual Testbeds for Planetary Exploration: The Self Localization Aspect, RWTH Aachen University Björn Sondermann Markus Emde Jürgen Roßmann 1

2 Content Previous Work Self Localization in terrestrial forestry environments Self Localization Approach Visual GPS Adaption to extraterrestrial environments Landmark detection using stereo cameras The Virtual Testbed Sensor framework Generalized communication concept Results and Future Work 2

3 Previous Work: Self Localization in Forestry Environments Self Localization in forestry environments Laser scanners as primary sensors Tree map from aerial data GPS and compass for initialization 3

4 Self Localization VisualGPS 4

5 Approach and First Implementation Inflexible implementation Generalization was needed Sick 2d laser scanner on each side of forest machine A Tree is observed as group of convex data points Initializing pose with compass and GPS data Localizing module Monte Carlo method Particle filter Absolute pose estimation by minimizing distances of observed trees to trees of global tree map 5

6 VisualGPS A Generalized Self Localization Approach Abstract structure of components Sensors and databases are available in system layers Landmark detectors and localizer are exchangeable Generalized communication among all components 6

7 VisualGPS in Forestry Environment Generalized self localization approach for forestry environments Localizer module defines set of valid landmark types Primary and secondary sensors are connected likewise Landmarks can be detected by different sensors Navigation map generated from aerial images and satellite data 7

8 Adaption of VisualGPS to Extraterrestrial Environments 8

9 Sensors for Landmark Detection 2d laser scanners Nearly full 360 horizontal field of view Fast data acquisition Ideal for continuous, vertical geometry detection (i.e. trees) 3d laser scanners Big spherical field of view Very slow data acquisition heavy not appropriate for moving scenes or robots Stereo cameras Metric depth information from calibrated stereo camera Acquire color and depth information with high data rate Appropriate for color and depth features 9

10 Tree Detection in Stereo Images Detecting tree landmarks using stereo cameras 1. Semi global block matching results in dense disparity map 2. Tree trunks result in single colored disparity regions 3. Vertical dominant regions are tree candidates. 10

11 Rock Detection in Stereo Images Challenging detection due to arbitrary geometry of rocks 1. Depth gradient provides an indication of obstacles 2. Partial occlusion as additional indicator for obstacle edges 3. Sobel edge detector results in sharp edges at distance jumps Distances can be calculated by triangulation between stereo matches Additional use of laser scanners result in more accurate depth values 11

12 The Virtual Testbed 12

13 Simulated Sensors Sensor simulation in virtual environments Error modeling Sensor data visualization 13

14 Virtual Sensors Algorithmic results and recorded data can be treated as sensors Virtual Sensors are connected in the same manner as real and simulated sensors The combination of real, simulated and virtual sensors is easy Resulting in hybrid testbeds Visual GPS 14

15 Communication Concept Standardized communication using an input output handler Using one abstract base class for all types of transferable data Flexible connection for all kinds of components 15

16 Sensor Framework 16

17 Virtual Testbeds Summary Virtual Testbeds allow a focused view on every component Developing new algorithms is possible without real hardware Conceptual implementation with ideal simulated sensor data Robustness measurement by adding error models Smooth transition between simulated and real world tests Testing with slightly different parameters under constant conditions 17

18 Results and Future Work Results so far: Self Localization method approved in real forestry testbed A mean error of approx. 0.55m was measured by surveyor s office Involved modules and sensors are validated against real components Extrapolation to new environments is possible due to generalized implementation Future Work: New detecting algorithms for extraterrestrial landmarks Navigational map creation from images from landing (Project: FastMap ) Evaluation of self localization results in virtual testbed (Project: SELOK ) Validating new modules for virtual mobile robotics testbeds 18

19 Virtual Testbed for Planetary Exploration 19