Learn More
We propose a fundamentally novel approach to real-time visual odometry for a monocular camera. It allows to benefit from the simplicity and accuracy of dense tracking – which does not depend on visual features – while running in real-time on a CPU. The key idea is to continuously estimate a semi-dense inverse depth map for the current frame, which in turn(More)
— In this paper, we describe a system that enables a low-cost quadrocopter coupled with a ground-based laptop to navigate autonomously in previously unknown and GPS-denied environments. Our system consists of three components: a monocular SLAM system, an extended Kalman filter for data fusion and state estimation and a PID controller to generate steering(More)
We present a complete solution for the visual navigation of a small-scale, low-cost quadrocopter in unknown environments. Our approach relies solely on a monocular camera as the main sensor, and therefore does not need external tracking aids such as GPS or visual markers. Costly computations are carried out on an external laptop that communicates over(More)
— We present an approach that enables a low-cost quadrocopter to accurately fly various figures using vision as main sensor modality. Our approach consists of three components: a monocular SLAM system, an extended Kalman filter for data fusion and state estimation and a PID controller to generate steering commands. Our system is able to navigate in(More)
Figure 1: From left to right: AR demo application with simulated car. Corresponding estimated semi-dense depth map. Estimated dense collision mesh, fixed and shown from a different perspective. Photo of running system. The attached video shows the system in action. ABSTRACT We present a direct monocular visual odometry system which runs in real-time on a(More)
— We present a 25 g nano-quadrotor equipped with a micro PAL-camera and wireless video transmitter, with which we demonstrate autonomous hovering and figure flying using a visual-inertial SLAM system running on a ground-based laptop. To our knowledge this is the lightest quadrotor capable of visual-inertial navigation with off-board processing. Further we(More)
— We propose a real-time, direct monocular SLAM method for omnidirectional or wide field-of-view fisheye cameras. Both tracking (direct image alignment) and mapping (pixel-wise distance filtering) are directly formulated for the unified omnidirectional model, which can model central imaging devices with a field of view well above 150 •. This is in stark(More)
Most current approaches to street-scene 3D reconstruction from a driving car to date rely on 3D laser scanning or tedious offline computation from visual images. In this paper, we compare a real-time capable 3D reconstruction method using a stereo extension of large-scale direct SLAM (LSD-SLAM) with laser-based maps and traditional stereo reconstructions(More)