Dirk Langer

A behavior-based system for off-road navigation

We describe a core system for autonomous navigation in outdoor natural terrain. The system consists of three parts: a perception module that processes range images to identify untraversable regions of the terrain, a local map management module that maintains a representation of the environment in the vicinity of the vehicle, and a planning module that issues commands to the vehicle controller. We illustrate our approach by an experiment in which a vehicle travelled autonomously for one kilometer through unmapped cross-country terrain. >

Active laser radar for high-performance measurements

Laser scanners, or laser radars (ladar), have been used for a number of years for mobile robot navigation and inspection tasks. Although previous scanners were sufficient for low speed applications, they often did not have the range or angular resolution necessary for mapping at the long distances. Many also did not provide an ample field of view with high accuracy and high precision. In this paper we will present the development of state-of-the-art, high speed, high accuracy, 3D laser radar technology. This work has been a joint effort between CMU and K2T and Z+F. The scanner mechanism provides an unobstructed 360/spl deg/ horizontal field of view, and a 70/spl deg/ vertical field of view. Resolution of the scanner is variable with a maximum resolution of approximately 0.06 degrees per pixel in both azimuth and elevation. The laser is amplitude-modulated, continuous-wave with an ambiguity interval of 52 m, a range resolution of 1.6 mm, and a maximum pixel rate of 625 kHz. This paper will focus on the design and performance of the laser radar and will discuss several potential applications for the technology. It reports on performance data of the system including noise, drift over time, precision, and accuracy with measurements. Influences of ambient light, surface material of the target and ambient temperature for range accuracy are discussed. Example data of applications will be shown and improvements will also be discussed.

Imaging Ladar for 3-D Surveying and CAD Modeling of Real-World Environments:

To establish mobile robot operations and to realize survey and inspection tasks, robust and precise measurements of the geometry of the 3-D environment is a required basic sensor technology. For visual inspection, surface classification, and documentation purposes, however, additional information concerning reflectance of measured objects is necessary. High-speed acquisition of both geometric and visual information is achieved by the described active ladar, developed by Zoller and Fröhlich (Z+F). In contrast to other range-sensing devices, the Z+F system is designed for high-speed and high-performance operation in real indoor and outdoor environments, emitting a minimum of near-infrared laser energy. It integrates a single-point laser measurement system and a mechanical deflection system for 3-D environmental measurements. Experimental results are reported from surface inspections in tunnels, the generation of 3-D CAD models of a work cell in an automotive manufacturing plant, the modeling of free-form surfaces such as historic sculptures, and applications in mobile robot navigation.

Fusing radar and vision for detecting, classifying and avoiding roadway obstacles

This paper describes an integrated MMW radar and vision sensor system for autonomous on-road navigation. The radar sensor has a range of approximately 200 metres and uses a linear array of receivers and wavefront reconstruction techniques to compute range and bearing of objects within the field of view. It is integrated with a vision based lane keeping system to accurately detect and classify obstacles with respect to the danger they pose to the vehicle and to execute required avoidance maneuvres.

Building qualitative elevation maps from side scan sonar data for autonomous underwater navigation

Deriving a terrain model from sensor data is an important task for the autonomous navigation of a mobile robot. An approach is presented for autonomous underwater vehicles using a side scan sonar system. Some general aspects of the type of data and filtering techniques to improve it are discussed. An estimated bottom contour is derived using a geometric reflection model and information about shadows and highlights. Several techniques of surface reconstruction and their limitations are presented. A method is presented for feature extraction which is important for future data matching/fusion procedures.<<ETX>>

Sonar Based Outdoor Vehicle Navigation And Collision Avoidance

Abstruct - Detecting unexpected obstacles and avoiding collisions is an important task for any autonomous mobile system. This paper describes an approach using a sonar system that we implemented for the autonomous land vehicle Navlab. The general hardware configuration of the system is shown, followed by a description of how the system builds a local grid map of its environment. The information collected in the map can then be used for a variety of applications in vehicle navigation like collision avoidance, feature tracking and parking. A simple algorithm was implemented that can track a static feature such as a rail, wall or an array of parked cars and use this information to drive the vehicle. Methods for filtering the raw data and generating the steering commands are discussed and the implementation for collision avoidance and its integration with other vehicle systems is described. I. INTRODUCTION The autonomous land vehicle Navlab has already successfully been driven on roads and cross country. Different sensors are used to perceive the structure of the environment and navigate the vehicle under a variety of conditions as described for example in [SI. The sensors mainly employed so far were colour video

Imaging laser scanners for 3-D modeling and surveying applications

In order to establish mobile robot operations and to realize survey and inspection tasks, robust and precise measurements of the geometry of the 3-D environment is a required basic sensor technology. For visual inspection, surface classification, and documentation purposes, however additional information concerning reflectance of measured objects is necessary. High-speed acquisition of both geometric and visual information is achieved by the described active laser radar developed at Zoller+Frohlich (Z+F). In contrast to other range sensing devices, the Z+F system is designed for high-speed and high-performance operation in real indoor and outdoor environments, emitting a minimum of near-infrared laser energy. It integrates a single-point laser measurement system and a mechanical deflection system for 3D environmental measurements. Experimental results are reported from surface inspections in tunnels, the generation of 3D CAD models of a work cell in an automotive manufacturing plant and the modeling of free form surfaces such as historic sculptures.

High-performance laser range scanner

Laser scanners, or ladars, have been used for a number of years for mobile robot navigation. Although previous scanners were sufficient for low-speed navigation, they often did not have the range or angular resolution necessary for mapping at the long distances required by high-speed navigation. Many also did not provide an ample field of view. In this paper we will present the development of state-of-the-art, high speed, high accuracy, laser range scanner technology. This work has been a joint effort between CMU and K2T in Pittsburgh and Zoller + Friehlich in Wangen, Germany. The scanner mechanism provides an unobstructed 360 degrees horizontal field of view, and a 30 degree vertical field of view. Resolution of the scanner is variable with a maximum resolution of approximately 0.06 degrees per pixel in both azimuth and elevation. The laser is amplitude-modulated, continuous-wave with an ambiguity interval of 52 metes, a range resolution of 1.6 mm, and a maximum pixel rate of 500 kHz. This paper will focus on the design and performance of the scanner mechanism and will discuss several potential applications for the technology. One application, obstacle detection for automated highway applications will be discussed in more detail. Example data will be shown and current mechanism improvements from the CMU prototype will also be discussed.

Sensor-friendly vehicle and roadway systems

Sensor-friendly vehicle and roadway systems consist of complementary signal sensor and reflector or transmitter technologies, which provide information about the threat of a collision. These technologies can be composed into cooperative collision avoidance systems, which can supplement or replace single vehicle-based systems. Experiments were run on the four most promising technologies to determine their performance and reliability; the four technologies were passive license plates with enhanced radar return, roadside obstacle-mounted radar-reflecting corner cubes, fluorescent paint for lane and obstacle marking, and light emitting diode brake-light messaging. These technologies all focus on improving the signal-to-noise ratio of the collision avoidance sensor. We believe that experimental results indicate that further proof-of-concept refinements are needed, but in general these systems represent technologically sound, cooperative vehicle-roadway components and that sensor friendly systems could eventually translate into a significant benefit in terms of lives saved.

Range Sensor Based Outdoor Vehicle Navigation, Collision Avoidance and Parallel Parking

Detecting unexpected obstacles and avoiding collisions is an important task for any autonomous mobile system. This article describes GANESHA (Grid based Approach for Navigation by Evidence Storage and Histogram Analysis), a system using sonar that we implemented for the autonomous land vehicle Navlab. The general hardware configuration of the system is shown, followed by a description of how the system builds a local grid map of its environment. The information collected in the map can then be used for a variety of applications in vehicle navigation like collision avoidance, feature tracking and parking. An algorithm was implemented that can track a static feature such as a rail, wall or an array of parked cars and use this information to drive the vehicle. Methods for filtering the raw data and generating the steering commands are discussed and the implementation for collision avoidance, parallel parking and its integration with other vehicle systems is described.