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We address the problem of on-line volumetric map creation of unknown environments and planning of safe trajectories. The sensor used for this purpose is a stereo camera. Our system is designed to work in GPS denied areas. We design a keyframe based hybrid SLAM algorithm which combines feature-based stereo SLAM and direct stereo SLAM. We use it to grow the map while keeping track of the camera pose...
This work presents KMVO, a ground plane based visual odometry that utilizes the vehicle's kinematic model to improve accuracy and robustness. Instead of solving a generic image alignment problem, the motion parameters of a differential drive vehicle can be directly estimated from RGB- D image data. In addition, a method for outlier rejection is presented that can deal with large percentages of outliers...
A fundamental task of automated guided vehicles is transporting heavy payloads. These payloads are often given in the form of large containers that are mounted onto a cart with four caster wheels. In this paper we investigate a combined detection and control architecture that allows an AGV to reliably detect and acquire such containers at any location, independently of a global localization system...
Automated guided vehicles (AGVs) are useful for a variety of transportation tasks. They usually detect obstacles on the path they are following using 2D laser scanners. If an AGV should be deployed in a shared space with people, 3D information has to be considered as well to detect unforeseen obstacles. These can be small objects on the floor or overhanging parts of larger objects, which cannot be...
In this paper we present a method for calculating inertial motion feedback in a teleoperation setup. For this we make a distinction between vehicle-state feedback that depends on the physical motion of the remote vehicle, and task-related motion feedback that provides information about the teleoperation task. By providing motion feedback that is independent of vehicle motion we exploit the spatial...
Visual odometry, especially using a forward-looking camera only, can be challenging: It is doomed to fail from time to time and will inevitably drift in the long run. We accept this fact and present methods to cope with and correct the effects for an autonomous MAV using an RGBD camera as its main sensor. We propose correcting drift and failure in visual odometry by combining its pose estimates with...
The correct classification of the surrounding terrain is an important ability of a mobile robot that drives in outdoor environments. Our robot uses a 3D LIDAR and a camera to classify terrain as either asphalt, cobblestones, grass, or gravel. We build on previous work where we modeled the terrain as a Conditional random field to account for spatial dependencies, which improved results substantially...
We present a fast and simple method for solving the perspective-three-point (P3P) problem. The problem is specified as finding the position and orientation of a camera from a single image, showing three points, while the position of the corresponding points in the world is known. Our approach is based on a new geometric parametrization, yielding simpler algebraic terms to compute, compared to all...
This paper extends a monocular visual simultaneous localization and mapping (SLAM) system to utilize two cameras with non-overlap in their respective field of views (FOVs). We achieve using it to enable autonomous navigation of a micro aerial vehicle (MAV) in unknown environments. The methodology behind this system can easily be extended to multi-camera rigs, if the onboard computation capability...
In this paper we investigate the effectiveness of SURF features for visual terrain classification for outdoor flying robots. A quadrocopter fitted with a single camera is flown over different terrains to take images of the ground below. Each image is divided into a grid and SURF features are calculated at grid intersections. A classifier is then used to learn to differentiate between different terrain...
We present a method of utilizing depth information as provided by RGBD sensors for robust real-time visual simultaneous localisation and mapping (SLAM) by augmenting monocular visual SLAM to take into account depth data. This is implemented based on the feely available software “Parallel Tracking and Mapping” by Georg Klein. Our modifications allow PTAM to be used as a 6D visual SLAM system even without...
In this paper we investigate SURF features for visual terrain classification for outdoor mobile robots. The image is divided into a grid and SURF features are calculated on the intersections of this grid. These features are then used to train a classifier that can differentiate between different terrain classes. Images of five different terrain types are taken using a single camera mounted on a mobile...
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