Local Perception for Mobile Robot Navigation in Natural Terrain: Two Approaches

Robotics Institut

3-D Measurements From Imaging Laser Radars: How Good Are They?

The authors analyze a class of imaging range finders-amplitude-modulated continuous-wave laser radars-in the context of computer vision and robotics. The analysis develops measurement models from the fundamental principles of laser radar operation, and identifies the nature and cause of key problems that plague measurements from this class of sensors. They classify the problems as fundamental (e.g. related to the signal-to-noise ratio), as architectural (e.g. limited by encoding distance by angles (0.2π)), and as artifacts of particular hardware implementations (e.g. insufficient temperature compensation). Experimental results from two different scanning laser range finders designed for autonomous navigation illustrate and support the analysi

3-D Measurements From Imaging Laser Radars: How Good Are They?

In this paper we analyse a class of imaging range finders —amplitude-modulated continuous-wave laser radars in the context of computer vision and robotics. The analysis develops measurement models from the fundamental principles of laser radar operation and identifies the nature and cause of key problems that affect measurements from this class of sensors. We classify the problems as fundamental (e.g. related to the signal-tonoise ratio), as architectural (e.g. limited by encoding distance by angles in [0, 2π]) and as artifacts of particular hardware implementations (e.g. insufficient temperature compensation). Experimental results from two different devices — scanning laser rangefinders designed for autonomous navigation — illustrate and support the analysis

Stereo Driving and Position Estimation for Autonomous Planetary Rovers

In this paper we present two new approaches to planetary rover perception. One approach concerns stereo driving without 3-D reconstruction. This approach begins with weakly calibrated stereo images, and evaluates the traversability of terrain using shape indicators such as relative slope and relative elevation. The approach then evaluates candidate paths based on the traversability analysis and generates the best path. The second approach involves estimating vehicle position by observing the Sun. At a given time, a measurement of the Sun's altitude constrains the observer to lie on a circle on the terrestrial surface called the circle of equal altitude. We determine the position of the observer by intersecting circles of equal altitude identified at different times. We are validating experimentally both approaches in unstructured, outdoor environments with several wheeled rovers, Future efforts will transfer the developed technology into Lunar Rover demonstration and flight programs

First Results in Terrain Mapping for a Roving Planetary Explorer

To perform planetary exploration without human supervision, a complete autonomous rover must be able to model its environment while exploring its surroundings. We present a new algorithm to construct a geometric terrain representation from a single range image. The form of the representation is an elevation map that includes uncertainty, unknown areas, and local features. By virtue of working in spherical-polar space, the algorithm is independent of the desired map resolution and the orientation of the sensor, unlike other algorithms that work in Cartesian space. We also describe new methods to evaluate regions of the constructed elevation maps to support legged locomotion over rough terrain

Terrain Mapping for a Roving Planetary Explorer

The main task of perception for autonomous vehicles is to build a representation of the observed environment in order to carry out a mission. In particular, terrain modeling, that is modeling the geometry of the environment observed by the vehicle's semors, is crucial for autonomous underwater exploration. The purpose of this work is to analyze the components of the terrain modeling task, to investigate the algorithms and representations for this task, and to evaluate them in the context of real applications. Terrain representation is an issue that is of interest in many areas of mobile robotics, such as land vehicles, planetary explorers, etc. This paper surveys some of the ideas developed in those areas and their relevance to the underwater navigation problem. Terrain modeling is divided into three parts: structuring sensor data, extracting features, and merging and updating terrain models

Experience with Rover Navigation for Lunar-Like Terrains

Reliable navigation is critical for a lunar rover, both for autonomous traverses and safeguarded, remote teleoperation. This paper describes an implemented system that has autonomously driven a prototype wheeled lunar rover over a kilometer in natural, outdoor terrain. The navigation system uses stereo terrain maps to perform local obstacle avoidance, and arbitrates steering recommendations from both the user and the rover. The paper describes the system architecture, each of the major components, and the experimental results to date