An open source and open hardware embedded metric optical flow CMOS camera for indoor and outdoor applications

Honegger, Dominik; Meier, Lorenz; Tanskanen, Petri; Pollefeys, Marc

doi:10.1109/icra.2013.6630805

Cited by 257 publications

(205 citation statements)

References 8 publications

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“…However, this work did not consider the issue of determining the unknown scene scale factor since the proposed control approach was implemented by only relying on the non-metric linear velocity directly obtained from a monocular camera. An approach combining optical flow decomposition and sensor fusion for metric scale estimation was instead presented in [14] by developing a small sensor for velocity estimation onboard UAVs. However, the proposed sensor relied on a ground facing sonar for metric scale estimation, thus limiting the vehicle to near ground operations within the range of the sonar.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear ego-motion estimation from optical flow for online control of a quadrotor UAV

Grabe

Bülthoff

Scaramuzza

et al. 2015

The International Journal of Robotics Research

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Abstract-For the control of Unmanned Aerial Vehicles (UAVs) in GPS-denied environments, cameras have been widely exploited as main sensory modality for addressing the UAV state estimation problem. However, the use of visual information for ego-motion estimation presents several theoretical and practical difficulties, such as data association, occlusions, and lack of direct metric information when exploiting monocular cameras. In this paper, we address these issues by considering a quadrotor UAV equipped with an onboard monocular camera and an Inertial Measurement Unit (IMU). First, we propose a robust ego-motion estimation algorithm for recovering the UAV scaled linear velocity and angular velocity from optical flow by exploiting the so-called continuous homography constraint in presence of planar scenes. Then, we address the problem of retrieving the (unknown) metric scale by fusing the visual information with measurements from the onboard IMU. To this end, two different estimation strategies are proposed and critically compared: a first one exploiting the classical Extended Kalman Filter (EKF) formulation, and a second one based on a novel nonlinear estimation framework. The main advantage of the latter scheme lies in the possibility of imposing a desired transient response to the estimation error when the camera moves with a constant acceleration norm w.r.t. the observed plane. We indeed show that, when compared against the EKF on the same trajectory and sensory data, the nonlinear scheme yields considerably superior performance in terms of convergence rate and predictability of the estimation. The paper is then concluded by an extensive experimental validation, including an onboard closed-loop control of a real quadrotor UAV meant to demonstrate the robustness of our approach in real-world conditions.

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Section: Introductionmentioning

confidence: 99%

Nonlinear ego-motion estimation from optical flow for online control of a quadrotor UAV

Grabe

Bülthoff

Scaramuzza

et al. 2015

The International Journal of Robotics Research

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“…Although both range and accuracy of ultrasonic sensors are very limited, they are very well suited for perceiving even small obstacles such as tree branches, overhead power cables and transmission lines. For localization and state estimation, we use an optical flow camera (Honegger et al, 2013) in addition to the two stereo camera pairs and the 3D laser scanner. It is pointing downwards to the Figure 2: Schematic overview of the onboard communication on our UAV.…”

Section: System Design and Sensor Setupmentioning

confidence: 99%

Towards Multimodal Omnidirectional Obstacle Detection for Autonomous Unmanned Aerial Vehicles

Holz

Nieuwenhuisen

Droeschel

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Limiting factors for increasing autonomy and complexity of truly autonomous systems (without external sensing and control) are onboard sensing and onboard processing power. In this paper, we propose a hardware setup and processing pipeline that allows a fully autonomous UAV to perceive obstacles in (almost) all directions in its surroundings. Different sensor modalities are applied in order take into account the different characteristics of obstacles that can commonly be found in typical UAV applications. We provide a complete overview on the implemented system and present experimental results as a proof of concept.

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“…Then a can be replaced by a , T total = T 80% , and R can be computed in the same form as (29), (30), (31), (32).…”

Section: Acceleration Controllermentioning

confidence: 99%

Design and Implementation of a Low Cost Mini Quadrotor for Vision Based Maneuvers in GPS Denied Environments

2016

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This paper presents the design and implementation detail of an advanced mini quadrotor system, including the low cost commercialoff-the-shelf (COTS) electronics and advanced control algorithm. The proposed quadrotor has a gross takeoff weight of 758 g and 360 mm frame diagonal size. It is capable of semi-autonomous manoeuvre in GPS denied environments, solely relying on onboard sensors and computers. A globally defined quadrotor model is formularised, and a nonlinear velocity tracking controller is implemented on the special Euclidean group SE(3). An optical flow and ultrasonic based onboard downward-facing camera is used as the primary sensor to provide velocity and altitude measurement feedback for the controller. The control and sensor fusion algorithm is developed under Arduino compatible open source electronics.

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An open source and open hardware embedded metric optical flow CMOS camera for indoor and outdoor applications

Cited by 257 publications

References 8 publications

Nonlinear ego-motion estimation from optical flow for online control of a quadrotor UAV

Nonlinear ego-motion estimation from optical flow for online control of a quadrotor UAV

Towards Multimodal Omnidirectional Obstacle Detection for Autonomous Unmanned Aerial Vehicles

Design and Implementation of a Low Cost Mini Quadrotor for Vision Based Maneuvers in GPS Denied Environments

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