Jean-Luc Bedwani

Over-the-horizon, autonomous navigation for planetary exploration

The success of NASAs Mars exploration rovers has demonstrated the important benefits that mobility adds to planetary exploration. Very soon, mission requirements will impose that planetary exploration rovers drive over-the-horizon in a single command cycle. This require an evolution of the methods and technologies currently used. This paper presents experimental validation of our over-the-horizon autonomous planetary navigation. We present our approach to 3D terrain reconstruction from large sparse range data sets, localization and autonomous navigation in a Mars-like terrain. Our approach is based on on-line acquisition of range scans, map construction from these scans, path planning and navigation using the map. An autonomy engine supervises the whole process ensuring the safe navigation of the planetary rover. The outdoor experimental results demonstrate the effectiveness of the reconstructed terrain model for rover localization, path planning and motion execution scenario as well as the autonomy capability of our approach.

Rough Terrain Reconstruction for Rover Motion Planning

A two-step approach is presented to generate a 3D navigable terrain model for robots operating in natural and uneven environment. First an unstructured surface is built from a 360 degrees field of view LIDAR scan. Second the reconstructed surface is analyzed and the navigable space is extracted to keep only the safe area as a compressed irregular triangular mesh. The resulting mesh is a compact terrain representation and allows point-robot assumption for further motion planning tasks. The proposed algorithm has been validated using a large database containing 688 LIDAR scans collected on an outdoor rough terrain. The mesh simplification error was evaluated using the approximation of Hausdorff distance. In average, for a compression level of 93.5%, the error was of the order of 0.5 cm. This terrain modeler was deployed on a rover controlled from the International Space Station (ISS) during the Avatar Explore Space Mission carried out by the Canadian Space Agency in 2009.

Path Planning for Planetary Exploration

In this paper we present the work done at the Canadian Space Agency on the problem of planetary exploration. One of the main goals is the over-the-horizon navigation of a mobile robot on a Mars like environment. A key component is the ability to plan a path using maps of different resolutions and also to refine/replan when more data becomes available. Our algorithms on path planning and path segmentation are presented together with results from two years of experiments in realistic conditions.

Autonomous over-the-horizon navigation using LIDAR data

In this paper we present the approach for autonomous planetary exploration developed at the Canadian Space Agency. The goal of this work is to enable autonomous navigation to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. We employ LIDAR range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. Irregular Triangular Meshes (ITMs) are used for representing the environment, providing an accurate, yet compact, spatial representation. In this paper a novel path-planning technique through the ITM is introduced, which guides the rover through flat terrain and safely away from obstacles. Experiments performed in CSA’s Mars emulation terrain, validating our approach, are also presented.

Autonomous planetary exploration using LIDAR data

In this paper we present the approach for autonomous planetary exploration developed at the Canadian Space Agency. The goal of this work is to autonomously navigate to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. We employ LIDAR range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. Irregular Triangular Meshes (ITMs) are used for representing the environment providing an accurate yet compact spatial representation. In this paper a novel path-planning technique through the ITM is introduced, which guides the rover through flatter terrain and safely away from obstacles. Experiments performed in CSAs Mars emulation terrain that validate our approach are also presented.

Terrain Modelling for Planetary Exploration

The success of NASAs Mars Exploration Rovers has demonstrated the important benefits that mobility adds to planetary exploration. Very soon, mission requirements will impose that planetary exploration rovers drive autonomously in unknown terrain. This will require an evolution of the methods and technologies currently used. This paper presents our approach to 3D terrain reconstruction from large sparse range data sets, and the data reduction achieved through decimation. The outdoor experimental results demonstrate the effectiveness of the reconstructed terrain model for different types of terrain. We also present a first attempt to classify the terrain based on the scans properties.

Experimental Results for Over-the-Horizon Planetary Exploration Using a LIDAR Sensor

In this paper we present the experimental results validating the approach for autonomous planetary exploration developed by the Canadian Space Agency (CSA). The goal of this work is to autonomously navigate to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. We employ LIDAR range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. Irregular triangular meshes (ITM) are used for representing the environment providing an accurate yet compact spatial representation. In this paper after a brief overview of the proposed approach, we discuss the terrain modelling used. A variety of experiments performed in CSA’s Mars emulation terrain that validate our approach are also presented.

Multi-Layer Atlas System for Map Management

Next generation planetary rovers will require greater autonomous navigation capabilities. Such requirements imply the management of potentially large and rich geo-referenced data sets stored in the form of maps. This paper presents the design of a data management system that can be used in the implementation of autonomous navigation schemes for planetary rovers. It also outlines an approach that dynamically manages a variety of data content and the uncertainty of the spatial relationship between two maps, in addition the proposed framework provides basic path planning operations through maps, and the correlation of maps in localization operations. Timing results from a rich data set demonstrate the efficiency of the proposed framework. In addition, experimental results on the usage of our Atlas management system by a rover performing autonomous navigation operations are also presented.