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Matthies, L.

Publications and source records attributed to Matthies, L..

At least 19 records

Online Photometric Calibration of Automatic Gain Thermal Infrared Cameras

Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance of traditional computer vision techniques developed for electro-optical imagery does not directly translate to the thermal domain due to two major reasons: these algorithms require photometric assumptions to hold, and methods for photometric calibration of RGB cameras cannot be applied to thermal-infrared cameras due to difference in data acquisition and sensor phenomenology. In this paper, we take a step in this direction, and introduce a novel algorithm for online photometric calibration of thermalinfrared cameras. Our proposed method does not require any specific driver/hardware support and hence can be applied to any commercial off-the-shelf thermal IR camera. We present this in the context of visual odometry and SLAM algorithms, and demonstrate the efficacy of our proposed system through extensive experiments for both standard benchmark datasets, and real-world field tests with a thermal-infrared camera in natural outdoor environments.

Daftry, Shreyansh

Stereo Vision-Based Obstacle Avoidance for Micro Air Vehicles Using an Egocylindrical Image Space Represntation

Micro air vehicles which operate autonomously at low altitude in cluttered environments require a method for on-board obstacle avoidance for safe operation. Prior approaches can be divided between purely reactive approaches, mapping low-level visual features directly to headings to maneuver the vehicle around the obstacle, and deliberative methods that use on-board 3-D sensors to create a 3-D, voxel-based world model, which is then used to generate collision free 3-D trajectories. In this paper, we use forward-looking stereo vision with a large horizontal and vertical field of view and project range from stereo into a novel robot-centered, cylindrical, inverse range map we call an egocylinder. With this implementation we reduce the complexity of our world representation from a 3D map to a 2.5D image space representation, which supports very efficient motion planning and collision-checking. Configuration space expansion is done very efficiently on the egocylinder as an image processing function. Deploying a fast reactive motion planner directly on the configuration space expanded egocylinder image, we demonstrate the effectiveness of this new approach experimentally in an indoor environment.

Micro air vehicles

Foliage discrimination using a rotating ladar

We present a real time algorithm that detects foliage using range from a rotating laser. Objects not classified as foliage are conservatively labeled as non-driving obstacles. In contrast to related work that uses range statistics to classify objects, we exploit the expected localities and continuities of an obstacle, in both space and time. Also, instead of attempting to find a single accurate discriminating factor for every ladar return, we hypothesize the class of some few returns and then spread the confidence (and classification) to other returns using the locality constraints. The Urbie robot is presently using this algorithm to descriminate drivable grass from obstacles during outdoor autonomous navigation tasks.

Autonomous navigation range robots

Multibaseline stereo system for evaluation of binocular stereo

In this paper, we provide both a system description and a detailed overview of a novel depth-based multibaseline stereo algorithm. Our new algorithm avoids the need for pairwise camera rectification. We conclude with several simulations and real world experiments to verify our results.

multibaseline

Multi-sensor, high speed autonomous stair climbing

In this paper we present the design and implementation of a new set of estimation and control algorithms that increase the speed and effectiveness of stair climbing.

mobile robotics estimation control machine vision

Fast and reliable obstacle detection and segmentation for cross-country navigation

Obstacle detection is one of the main components of the control system of autonomous vehicles. In the case of indoor/urban navigation, obstacles are typically defined as surface points that are higher than the ground plane. This characterization, however, cannot be used in cross-country and unstructured environments, where the notion of ground plane is often not meaningful.

autonomous navigation obstacle detection terrain p

Multi-resolution mapping using surface, descent and orbit images

Our objective is to produce high-accuracy maps of the terrain elevation at landing sites on planetary bodies through the use of all available image data. These technologies are important for performing rover navigation in future space missions and the maps provide a tool for coordinating rovers in a robotic colony.

localization

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

A Portable, Autonomous, Urban Reconnaissance Robot

Portable mobile robots, in the size class of 20 kg or less, could be extremely valuable as autonomous reconnaissance platforms in urban hostage situations and disaster relief.

mobile robot autonomous navigation

Vision-Guided Autonomous Stair Climbing

The Tactical Mobile Robot (TMR) program calls for autonomous mobility in an urban environment. Among all man-made structures which pose as barriers for a mobile robot, stairs are the most obvious and ubiquitous structure an autonomous urban robot needs to be able to handle.

Mobile