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Vision-based state estimation for autonomous rotorcraft MAVs in complex environments
- In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA
, 2013
"... Abstract-In this paper, we consider the development of a rotorcraft micro aerial vehicle (MAV) system capable of visionbased state estimation in complex environments. We pursue a systems solution for the hardware and software to enable autonomous flight with a small rotorcraft in complex indoor and ..."
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Abstract-In this paper, we consider the development of a rotorcraft micro aerial vehicle (MAV) system capable of visionbased state estimation in complex environments. We pursue a systems solution for the hardware and software to enable autonomous flight with a small rotorcraft in complex indoor and outdoor environments using only onboard vision and inertial sensors. As rotorcrafts frequently operate in hover or nearhover conditions, we propose a vision-based state estimation approach that does not drift when the vehicle remains stationary. The vision-based estimation approach combines the advantages of monocular vision (range, faster processing) with that of stereo vision (availability of scale and depth information), while overcoming several disadvantages of both. Specifically, our system relies on fisheye camera images at 25 Hz and imagery from a second camera at a much lower frequency for metric scale initialization and failure recovery. This estimate is fused with IMU information to yield state estimates at 100 Hz for feedback control. We show indoor experimental results with performance benchmarking and illustrate the autonomous operation of the system in challenging indoor and outdoor environments.
Gps-denied indoor and outdoor monocular vision aided navigation and control of unmanned aircraft
- Journal of Field Robotics
, 2013
"... GPS-denied closed-loop autonomous control of unstable Unmanned Aerial Vehicles (UAVs) such as rotorcraft using information from a monocular camera has been an open problem. Most proposed Vision aided Inertial Navigation Systems (V-INS) have been too compu-tationally intensive or do not have sufficie ..."
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GPS-denied closed-loop autonomous control of unstable Unmanned Aerial Vehicles (UAVs) such as rotorcraft using information from a monocular camera has been an open problem. Most proposed Vision aided Inertial Navigation Systems (V-INS) have been too compu-tationally intensive or do not have sufficient integrity for closed-loop flight. We provide an affirmative answer to the question of whether V-INS can be used to sustain prolonged real-world GPS-denied flight by presenting a V-INS that is validated through autonomous flight-tests over prolonged closed-loop dynamic operation in both indoor and outdoor GPS-denied environments with two rotorcraft UAS. The architecture efficiently combines visual feature information from a monocular camera with measurements from inertial sensors. In-ertial measurements are used to predict frame-to-frame transition of online selected feature locations, and the difference between predicted and observed feature locations is used to bind in real-time the inertial measurement unit drift, estimate its bias, and account for initial misalignment errors. A novel algorithm to manage a library of features online is presented that can add or remove features based on a measure of relative confidence in each feature location. The resulting V-INS is sufficiently efficient and reliable to enable real-time imple-mentation on resource constrained aerial vehicles. The presented algorithms are validated on multiple platforms in real-world conditions: through a 16 minute flight test, including an autonomous landing, of a 66 kg rotorcraft UAV operating in an unconctrolled outdoor envi-ronment without using GPS and through a Micro-UAV operating in a cluttered, unmapped,
Vistas and wall-floor intersection features - enabling autonomous flight in man-made environments
- in Workshop on Visual Control of Mobile Robots
, 2012
"... Abstract — We propose a solution toward the problem of autonomous flight and exploration in man-made indoor environments with a micro aerial vehicle (MAV), using a frontal camera, a downward-facing sonar, and an IMU. We present a general method to detect and steer an MAV toward distant features that ..."
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Abstract — We propose a solution toward the problem of autonomous flight and exploration in man-made indoor environments with a micro aerial vehicle (MAV), using a frontal camera, a downward-facing sonar, and an IMU. We present a general method to detect and steer an MAV toward distant features that we call vistas while building a map of the environment to detect unexplored regions. Our method enables autonomous exploration capabilities while working reliably in textureless indoor environments that are challenging for traditional monocular SLAM approaches. We overcome the difficulties faced by traditional approaches with Wall-Floor Intersection Features, a novel type of low-dimensional landmarks that are specifically designed for man-made environments to capture the geometric structure of the scene. We demonstrate our results on a small, commercially available quadrotor platform. I.
Indoor Navigation with a Swarm of Flying Robots
"... Abstract — Swarms of flying robots are promising in many applications due to rapid terrain coverage. However, there are numerous challenges in realising autonomous operation in unknown indoor environments. A new autonomous flight methodology is presented using relative positioning sensors in referen ..."
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Abstract — Swarms of flying robots are promising in many applications due to rapid terrain coverage. However, there are numerous challenges in realising autonomous operation in unknown indoor environments. A new autonomous flight methodology is presented using relative positioning sensors in reference to nearby static robots. The entirely decentralised approach relies solely on local sensing without requiring absolute positioning, environment maps, powerful computation or longrange communication. The swarm deploys as a robotic network facilitating navigation and goal directed flight. Initial validation tests with quadrotors demonstrated autonomous flight within a confined indoor environment, indicating that they could traverse a large network of static robots across expansive environments. I.
Accurate Figure Flying with a Quadrocopter Using Onboard Visual and Inertial Sensing
"... Abstract — 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 ge ..."
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Abstract — 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 previously unknown indoor and outdoor environments at absolute scale without requiring artificial markers or external sensors. Next to a full description of our system, we introduce our scripting language and present several examples of accurate figure flying in the corresponding video submission. I.
Saliency detection and model-based tracking: a two part vision system for small robot navigation in forested environment
- in Proceedings of SPIE
, 2012
"... Towards the goal of fast, vision-based autonomous flight, localization, and map building to support local planning and control in unstructured outdoor environments, we present a method for incrementally building a map of salient tree trunks while simultaneously estimating the trajectory of a quadrot ..."
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Towards the goal of fast, vision-based autonomous flight, localization, and map building to support local planning and control in unstructured outdoor environments, we present a method for incrementally building a map of salient tree trunks while simultaneously estimating the trajectory of a quadrotor flying through a forest. We make significant progress in a class of visual perception methods that produce low-dimensional, geometric information that is ideal for planning and navigation on aerial robots, while directing computational resources using motion saliency, which selects objects that are important to navigation and planning. By low-dimensional geometric information, we mean coarse geometric primitives, which for the purposes of motion planning and navigation are suitable proxies for real-world objects. Additionally, we develop a method for summarizing past image measurements that avoids expensive computations on a history of images while maintaining the key non-linearities that make full map and trajectory smoothing possible. We demonstrate results with data from a small, commercially-available quad-rotor flying in a challenging, forested environment. 1.
Vision-Based Control of a Multi-Rotor Helicopter
, 2011
"... Autonomous air vehicles frequently rely on GPS as a primary source of state feedback. However, relying on GPS disallows operation in enclosed spaces, under heavy vegetation or near large obstacles since GPS does not provide sufficient accuracy in these environments. Similar work in GPS-denied naviga ..."
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Autonomous air vehicles frequently rely on GPS as a primary source of state feedback. However, relying on GPS disallows operation in enclosed spaces, under heavy vegetation or near large obstacles since GPS does not provide sufficient accuracy in these environments. Similar work in GPS-denied navigation uses laser-based odometry, structured-light or places visual markers in the environment. These approaches are not appropriate for operating in unstructured environments, therefore it is necessary to develop a system around more robust vision-based techniques. This work presents a method for controlling an autonomous, multi-rotor helicopter based on visual odometry which consists of two major sections. First, a method for developing an accurate dynamic model of a multi-rotor helicopter based on a combination of first priciples and emperical data is presented. This modeling technique is used to develop a control system which enables trajectory tracking. Second, a vision-based state-estimation technique is presented along with a hardware implementation that enables execution of the algorithms in real-time on board a small vehicle with strict payload constraints. The methods described are
Hovering quad-rotor control: A comparison of nonlinear controllers using visual feedback
, 2013
"... Abstract—This article presents a comparison of three control techniques: Nested Saturations, Backstepping and Sliding Modes. The control objective consists of obtaining the best control strategy to stabilize the position of a quad-rotor unmanned aerial vehicle (UAV) when using visual feedback. We pr ..."
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Abstract—This article presents a comparison of three control techniques: Nested Saturations, Backstepping and Sliding Modes. The control objective consists of obtaining the best control strategy to stabilize the position of a quad-rotor unmanned aerial vehicle (UAV) when using visual feedback. We propose a visionbased method to measure translational speed as well as the UAV 3D position in a local frame. The three selected controllers were implemented and tested in real-time experiments. The obtained results demonstrate the performance of such methodologies applied to the quad-rotor system. Index Terms—Autonomous helicopter, nested saturations, backstepping, sliding modes, visual feedback, position stabilization. I.
Sun ―Control System Design for Multi-Rotor MAV
- Journal of Theoretical and Applied Mechanics
"... Abstract MAVs (Micro Air Vehicles) have attracted more and more attention in recent years because of their wide applications, such as investigations of inhospitable environment, nuclear or hazardous material polluted regions and other inaccessible areas. In this paper, both attitude and altitude con ..."
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Abstract MAVs (Micro Air Vehicles) have attracted more and more attention in recent years because of their wide applications, such as investigations of inhospitable environment, nuclear or hazardous material polluted regions and other inaccessible areas. In this paper, both attitude and altitude controls of a Quad-Rotor type MAV are discussed and analyzed. To stabilize the attitude, one order memory based controller is selected, the performance of which is independent of the detail model information, leading to enhanced robustness. While for the altitude, a Linear Quadratic Gaussian (LQG) controller is proposed. The expe-rimental results of the real flight demonstrate the stability and robustness of the controllers. Key words: MAV, attitude control, altitude control, LQG, memory based control 1.
