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35
Visual odometry and mapping for autonomous flight using an RGB-D camera
- In Proc. of the Intl. Sym. of Robot. Research
, 2011
"... Abstract RGB-D cameras provide both a color image and per-pixel depth estimates. The richness of their data and the recent development of low-cost sensors have combined to present an attractive opportunity for mobile robotics research. In this paper, we describe a system for visual odometry and mapp ..."
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Cited by 77 (4 self)
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Abstract RGB-D cameras provide both a color image and per-pixel depth estimates. The richness of their data and the recent development of low-cost sensors have combined to present an attractive opportunity for mobile robotics research. In this paper, we describe a system for visual odometry and mapping using an RGB-D camera, and its application to autonomous flight. By leveraging results from recent state-of-the-art algorithms and hardware, our system enables 3D flight in cluttered environments using only onboard sensor data. All computation and sensing required for local position control are performed onboard the vehicle, reducing the dependence on unreliable wireless links. We evaluate the effectiveness of our system for stabilizing and controlling a quadrotor micro air vehicle, demonstrate its use for constructing detailed 3D maps of an indoor environment, and discuss its limitations. 1
A Fully Autonomous Indoor Quadrotor
"... Recently there has been an increased interest in the development of autonomous flying vehicles. Whereas most of the proposed approaches are suitable for outdoor operation, only a few techniques have been designed for indoor environments, where the systems cannot rely on GPS and therefore have to us ..."
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Cited by 33 (2 self)
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Recently there has been an increased interest in the development of autonomous flying vehicles. Whereas most of the proposed approaches are suitable for outdoor operation, only a few techniques have been designed for indoor environments, where the systems cannot rely on GPS and therefore have to use their exteroceptive sensors for navigation. In this paper we present a general navigation system which enables a small-sized quadrotor system to autonomously operate in indoor environments. To achieve this, we systematically extend and adapt techniques which have been successfully applied on ground robots. We describe all algorithms and present a broad set of experiments illustrating that they enable a quadrotor robot to reliably and autonomously navigate in indoor environments.
A flexible and scalable slam system with full 3d motion estimation
- in International Symposium on Safety, Security, and Rescue Robotics. IEEE
, 2011
"... Abstract—For many applications in Urban Search and Rescue (USAR) scenarios robots need to learn a map of unknown environments. We present a system for fast online learning of occupancy grid maps requiring low computational resources. It combines a robust scan matching approach using a LIDAR system w ..."
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Cited by 20 (3 self)
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Abstract—For many applications in Urban Search and Rescue (USAR) scenarios robots need to learn a map of unknown environments. We present a system for fast online learning of occupancy grid maps requiring low computational resources. It combines a robust scan matching approach using a LIDAR system with a 3D attitude estimation system based on inertial sensing. By using a fast approximation of map gradients and a multi-resolution grid, reliable localization and mapping capabilities in a variety of challenging environments are realized. Multiple datasets showing the applicability in an embedded handheld mapping system are provided. We show that the system is sufficiently accurate as to not require explicit loop closing techniques in the considered scenarios. The software is available as an open source package for ROS.
Learning Monocular Reactive UAV Control in Cluttered Natural Environments
, 1211
"... Abstract—Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straight-forward, as expensive sensors and monitoring devices can be employed. In contrast, obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAVs) which operate at low altitude in cluttered env ..."
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Cited by 19 (2 self)
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Abstract—Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straight-forward, as expensive sensors and monitoring devices can be employed. In contrast, obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAVs) which operate at low altitude in cluttered environments. Unlike large vehicles, MAVs can only carry very light sensors, such as cameras, making autonomous navigation through obstacles much more challenging. In this paper, we describe a system that navigates a small quadrotor helicopter autonomously at low altitude through natural forest environments. Using only a single cheap camera to perceive the environment, we are able to maintain a constant velocity of up to 1.5m/s. Given a small set of human pilot demonstrations, we use recent state-of-theart imitation learning techniques to train a controller that can avoid trees by adapting the MAVs heading. We demonstrate the performance of our system in a more controlled environment indoors, and in real natural forest environments outdoors. I.
Aerial service robotics: The AIRobots perspective
- in 2nd International Conference on Applied Robotics for the Power Industry
, 2012
"... Abstract—This paper presents the main vision and research ..."
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Cited by 12 (4 self)
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Abstract—This paper presents the main vision and research
3d indoor mapping for micro-uavs using hybrid range finders and multi-volume occupancy grids
- In RSS 2010 workshop on RGB-D: Advanced Reasoning with Depth Cameras
, 2010
"... Abstract — Autonomous micro-UAV navigation requires techniques that allow for the accurate mapping of unstructured 3D environments such as stairwells, tunnels, and caves. As a step towards that goal, this paper presents a system to build three-dimensional maps of rectilinear environments, where the ..."
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Cited by 7 (0 self)
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Abstract — Autonomous micro-UAV navigation requires techniques that allow for the accurate mapping of unstructured 3D environments such as stairwells, tunnels, and caves. As a step towards that goal, this paper presents a system to build three-dimensional maps of rectilinear environments, where the horizontal cross-section of the world is invariant at different heights. The assumption that the environment is structured makes our approach suitable for mapping of indoor spaces. One of the largest challenges in 3D mapping is correctly estimating the full 6-DOF pose of the vehicle. We present an approach that estimates the pose by fusing the information of an altimeter, an IMU, and a horizontally-mounted laser range-finder. A key step in the estimation is an orthogonal projection of the laser scan data, allowing for accurate scan matching in 2D. We also propose a novel map data structure called a Multi-Volume Occupancy Grid. MVOGs explicitly store information about both obstacles and free space. This allows us to correct previous potentially erroneous sensor readings by incrementally fusing in new sensor information. In turn, this enables extracting more reliable probabilistic information about the occupancy of 3D space. Observations are grouped together into continuous vertical volumes, which makes this new data structure considerably more space-efficient than point cloud or voxel-grid representations. I.
A.: Integrating sensor and motion models to localize an autonomous ar.drone
- International Journal of Micro Air Vehicles
, 2011
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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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Cited by 5 (1 self)
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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.
Trust-Driven Interactive Visual Navigation for Autonomous Robots
"... Abstract — We describe a model of “trust ” in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human’s expectatio ..."
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Cited by 3 (2 self)
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Abstract — We describe a model of “trust ” in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human’s expectations, with respect to task demands. Our trust model drives an adaptive mechanism that dynamically adjusts the robot’s autonomous behaviors, in order to improve the efficiency of the collaborative team. We illustrate this trust-driven methodology through an interactive visual robot navigation system. This system is evaluated through controlled user experiments and a field demonstration using an aerial robot. 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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Cited by 3 (0 self)
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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.
