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NASA NTRS2011

Unmanned Ground Vehicle Perception Using Thermal Infrared Cameras

The ability to perform off-road autonomous navigation at any time of day or night is a requirement for some unmanned ground vehicle (UGV) programs. Because there are times when it is desirable for military UGVs to operate without emitting strong, detectable electromagnetic signals, a passive only terrain perception mode of operation is also often a requirement. Thermal infrared (TIR) cameras can be used to provide day and night passive terrain perception. TIR cameras have a detector sensitive to either mid-wave infrared (MWIR) radiation (3-5?m) or long-wave infrared (LWIR) radiation (8-12?m). With the recent emergence of high-quality uncooled LWIR cameras, TIR cameras have become viable passive perception options for some UGV programs. The Jet Propulsion Laboratory (JPL) has used a stereo pair of TIR cameras under several UGV programs to perform stereo ranging, terrain mapping, tree-trunk detection, pedestrian detection, negative obstacle detection, and water detection based on object reflections. In addition, we have evaluated stereo range data at a variety of UGV speeds, evaluated dual-band TIR classification of soil, vegetation, and rock terrain types, analyzed 24 hour water and 12 hour mud TIR imagery, and analyzed TIR imagery for hazard detection through smoke. Since TIR cameras do not currently provide the resolution available from megapixel color cameras, a UGV's daytime safe speed is often reduced when using TIR instead of color cameras. In this paper, we summarize the UGV terrain perception work JPL has performed with TIR cameras over the last decade and describe a calibration target developed by General Dynamics Robotic Systems (GDRS) for TIR cameras and other sensors.

terrain classification↗

NASA NTRS1991

INS integrated motion analysis for autonomous vehicle navigation

The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.

Roberts, Barry↗

NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

The ability to detect and locate obstacles using on-board sensors and modify the nominal trajectory is necessary for safe landing of an autonomous lander on Mars. This paper examines some of the issues in the location of objects using a sequence of images from a passive sensor, and describes a Kalman filter approach to improve the range estimation to obstacles. The filter is also used to track features in the images leading to a significant reduction of search effort in the feature extraction step of the algorithm. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. An experiment is designed to acquire a sequence of images along with sensor motion parameters and the range estimation results using this imagery are presented.

Sridhar, B.↗

NASA NTRS1992

Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and four resulting datasets are discussed. Finally the performance of the range estimation algorithm is explored in detail based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Philip N.↗

NASA NTRS1992

Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and one of four resulting datasets is briefly discussed. Finally the performance of the range estimation algorithm is explored based on comparison of the range estimates with true range measurements collected during the flight experiment.

Smith, Phillip N.↗

NASA NTRS1992

Vision-based range estimation using helicopter flight data

Smith, Phillip N.↗

NASA NTRS1991

Status of automated nap-of-the-earth rotorcraft guidance

The status of automated nap-of-the-earth (NOE) flight guidance is discussed by examining two current research efforts that approach the problem of performing obstacle avoidance along a pre-planned course from different perspectives. The first, a real-time guidance system developed by Systems Technology Inc., focuses on the issue of pilot acceptable maneuvers, under the assumption of an ideal, but nonrealizable, obstacle detection system. The second, a system created at NASA Ames, concentrates on the utilization of realistic on-board sensor data for obstacle detection and avoidance-maneuver decisions. This paper examines the strengths and weaknesses of these two approaches, and how they might complement each other. The goal is an automatic NOE system that is both acceptable to pilots and capable of making intelligent use of realistic sensor information and path-selection logic.

Coppenbarger, Richard A.↗

NASA NTRS1992

Passive stereo range imaging for semi-autonomous land navigation

The paper examines the use of stereo vision (SV) for obstacle detection in semiautonomous land navigation. Feature-based and field-based paradigms for SV are reviewed. The paper presents stochastic models and simple, efficient stereo matching algorithms for the field-based approach and describes a near-real-time vision system using these algorithms. Experimental results illustrate aspects of the stochastic models and lead to the first semiautonomous traversals of natural terrain to use SV for obstacle detection.

Matthies, Larry↗

NASA NTRS1991

Vision based techniques for rotorcraft low altitude flight

An overview of research in obstacle detection at NASA Ames Research Center is presented. The research applies techniques from computer vision to automation of rotorcraft navigation. The development of a methodology for detecting the range to obstacles based on the maximum utilization of passive sensors is emphasized. The development of a flight and image data base for verification of vision-based algorithms, and a passive ranging methodology tailored to the needs of helicopter flight are discussed. Preliminary results indicate that it is possible to obtain adequate range estimates except at regions close to the FOE. Closer to the FOE, the error in range increases since the magnitude of the disparity gets smaller, resulting in a low SNR.

Sridhar, Banavar↗

NASA NTRS2009

Using Thermal Radiation in Detection of Negative Obstacles

A method of automated detection of negative obstacles (potholes, ditches, and the like) ahead of ground vehicles at night involves processing of imagery from thermal-infrared cameras aimed at the terrain ahead of the vehicles. The method is being developed as part of an overall obstacle-avoidance scheme for autonomous and semi-autonomous offroad robotic vehicles. The method could also be applied to help human drivers of cars and trucks avoid negative obstacles -- a development that may entail only modest additional cost inasmuch as some commercially available passenger cars are already equipped with infrared cameras as aids for nighttime operation.

Rankin, Arturo L.↗

NASA NTRS1975

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

Problems related to an unmanned exploration of the planet Mars by means of an autonomous roving planetary vehicle are investigated. These problems include: design, construction and evaluation of the vehicle itself and its control and operating systems. More specifically, vehicle configuration, dynamics, control, propulsion, hazard detection systems, terrain sensing and modelling, obstacle detection concepts, path selection, decision-making systems, and chemical analyses of samples are studied. Emphasis is placed on development of a vehicle capable of gathering specimens and data for an Augmented Viking Mission or to provide the basis for a Sample Return Mission.

Gisser, D. G.↗

NASA NTRS2000

Terrain Perception for DEMO III

The Demo III program has as its primary focus the development of autonomous mobility for a small rugged cross country vehicle. In this paper we report recent progress on both stereo-based obstacle detection and terrain cover color-based classification.

autonomous navigation color classification terrain↗

NASA NTRS1992

Reflexive Avoidance Of Obstacles By Robots

Array of sensors at elbow of robotic manipulator detects obstacles. Outputs of sensors processed into synthetic "force field" around each obstacle. Algorithm controlling manipulator uses "force field" to maneuver manipulator arm around each obstacle.

Vold, Havard I.↗

NASA NTRS1995

Model-Based Obstacle Detention From Image Sequences

This paper proposes a method for detecting obstacles on a runway from monocular image sequences. The surface of the runway is modeled as a plane and the model flow field corresponding to the runway is described by 8 coefficients. The set of 8 coefficients describing the initial model flow field is given by the data from Inertial Navigation System (INS). The uncertainties of this initial model flow field are estimated and used to obtain the accurate model flow field. The residual flow field after warping images by the accurate model flow field is computed by solving over determined gradient-based optical flow equations using a singular value decomposition (SVD). This SVD gives us a new insight of the uncertainties inherent in the optical flow computation. Those pixels with large residual flow vectors are considered as obstacles. Experimental results for two real image sequences are presented.

Sull, Sanghoon↗

NASA NTRS1974

Recognition of three dimensional obstacles by an edge detection scheme

The need for an obstacle detection system on the Mars roving vehicle was assumed, and a practical scheme was investigated and simulated. The principal sensing device on this vehicle was taken to be a laser range finder. Both existing and original algorithms, ending with thresholding operations, were used to obtain the outlines of obstacles from the raw data of this laser scan. A theoretical analysis was carried out to show how proper value of threshold may be chosen. Computer simulations considered various mid-range boulders, for which the scheme was quite successful. The extension to other types of obstacles, such as craters, was considered. The special problems of bottom edge detection and scanning procedure are discussed.

Reed, M. A.↗

NASA NTRS1991

Fuzzy Logic Path Planning System for Collision Avoidance by an Autonomous Rover Vehicle

Systems already developed at JSC have shown the benefits of applying fuzzy logic control theory to space related operations. Four major issues are addressed that are associated with developing an autonomous collision avoidance subsystem within a path planning system designed for application in a remote, hostile environment that does not lend itself well to remote manipulation of the vehicle involved through Earth-based telecommunication. A good focus for this is unmanned exploration of the surface of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. The four major issues addressed are: (1) avoidance of a single fuzzy moving obstacle; (2) back off from a dead end in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system.

Murphy, Michael G.↗

NASA NTRS1993

Fuzzy logic path planning system for collision avoidance by an autonomous rover vehicle

The Space Exploration Initiative of the United States will make great demands upon NASA and its limited resources. One aspect of great importance will be providing for autonomous (unmanned) operation of vehicles and/or subsystems in space flight and surface exploration. An additional, complicating factor is that much of the need for autonomy of operation will take place under conditions of great uncertainty or ambiguity. Issues in developing an autonomous collision avoidance subsystem within a path planning system for application in a remote, hostile environment that does not lend itself well to remote manipulation by Earth-based telecommunications is addressed. A good focus is unmanned surface exploration of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. Four major issues addressed are (1) avoidance of a fuzzy moving obstacle; (2) backoff from a deadend in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system. Examples of the need for collision avoidance by an autonomous rover vehicle on the surface of Mars with a moving obstacle would be wind-blown debris, surface flow or anomalies due to subsurface disturbances, another vehicle, etc. The other issues of backoff, sensor fusion, and adaptive learning are important in the overall path planning system.

Murphy, Michael G.↗

NASA NTRS1976

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Longendorfer, B. A.↗