Receding Horizon "Next-Best-View" Planner for 3D Exploration

Bircher, Andreas; Kamel, Mina; Alexis, Kostas; Oleynikova, Helen; Siegwart, Roland

doi:10.1109/icra.2016.7487281

Cited by 493 publications

(431 citation statements)

References 22 publications

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“…In [149] a path planning algorithm for autonomous exploration in bounded unknown environments has been presented. The core of this work is based on a receding horizon scheme.…”

Section: Guidancementioning

confidence: 99%

Survey on Computer Vision for UAVs: Current Developments and Trends

Kanellakis

Nikolakopoulos

2017

J Intell Robot Syst

295

120

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During last decade the scientific research on Unmanned Aerial Vehicless (UAVs) increased spectacularly and led to the design of multiple types of aerial platforms. The major challenge today is the development of autonomously operating aerial agents capable of completing missions independently of human interaction. To this extent, visual sensing techniques have been integrated in the control pipeline of the UAVs in order to enhance their navigation and guidance skills. The aim of this article is to present a comprehensive literature review on vision based applications for UAVs focusing mainly on current developments and trends. These applications are sorted in different categories according to the research topics among various research groups. More specifically vision based position-attitude control, pose estimation and mapping, obstacle detection as well as target tracking are the identified components towards autonomous agents. Aerial platforms could reach greater level of autonomy by integrating all these technologies onboard. Additionally, throughout this article the concept of fusion multiple sensors is highlighted, while an overview on the challenges C. Kanellakis ( ) · G. Nikolakopoulos Luleå University of Technology, Luleå, Sweden e-mail: christoforos.kanellakis@ltu.se G. Nikolakopoulos e-mail: geonik@ltu.se addressed and future trends in autonomous agent development will be also provided.

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“…In [149] a path planning algorithm for autonomous exploration in bounded unknown environments has been presented. The core of this work is based on a receding horizon scheme.…”

Section: Guidancementioning

confidence: 99%

Survey on Computer Vision for UAVs: Current Developments and Trends

Kanellakis

Nikolakopoulos

2017

J Intell Robot Syst

295

120

View full text Add to dashboard Cite

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“…This reconfiguration was purely on-line and based on converting 2D tracking to 3D motion. Similarly, a 3D exploration method employed the NBV approach to map a static environment about a mobile robot in [109].…”

Section: Single Sensor Reconfigurationmentioning

confidence: 99%

Multi-Camera Active-Vision for Markerless Shape Recovery of Unknown Deforming Objects

Nuger

Benhabib

2018

J Intell Robot Syst

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This thesis proposes a multi-camera active-vision reconfiguration system which selects camera poses online to improve the shape recovery of a priori unknown, markerless, deforming objects in dynamic environments. The objectives of shape recovery are defined as surface sampling accuracy, and shape completeness. The completeness objective is generalized for both solid and surface-based objects as the maximization of surface visibility. Thus, improving the recovered shape of target objects is shown to be analogous to maximizing the surface area visibility. This improvement is achieved through the on-line reconfiguration of multiple cameras. The system developed herein is composed of a shape recovery method, a robust tracking algorithm, and a multi-camera reconfiguration method.The shape recovery method is based on a modular fusion technique that produces a complete 3D mesh-model of the target object. The method fuses triangulation data with a visual hull to maximize recovery accuracy. The modularity of the method lies in the ability to modify data filtering techniques to improve modelling accuracy, and interchange stereo correspondence features. The adaptive particle filtering algorithm produces a deformation estimation of the recovered model from the tracking data. The algorithm automatically adapts to the quantity of tracking data available and changes in the object's dynamics. The modularity of the algorithm allows modifications in terms of the number of particles and motion models for task-specific implementations. The reconfiguration method consists of a robust stereovisibility objective function, workspace discretization, and a path planner. The complete system can iii improve the shape recovery of a priori unknown deforming objects in obstacle-laden environments when compared to static camera methods.To validate the proposed system, extensive simulations and experiments were conducted. The simulations tested the system in comparison to static multi-camera systems, and ideal camera placement where the object model was a priori known and the camera's dynamics were unconstrained. Simulation results showed the proposed methodology outperformed static cameras and approached the performance of ideal camera placement in a dynamic, obstacle-laden environment. The experimental results showed similar improvement in shape recovery when comparison to a static camera system in an obstacle-laden environment.iv

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“…Exploration specifically using multi-rotors has been shown in [12], [13] and [14], among others. In [12], the authors propose a frontier-based exploration strategy for quadrotors using the 3D occupancy map OctoMap [15].…”

Section: Related Workmentioning

confidence: 99%

“…In terms of exploration speed, however, their experiments show that the frontier exploration approach by [7] performs better. [14] revisits NBV-based exploration. Instead of sampling poses in the free space, feasible trajectories are sampled using RRT* [16].…”

Section: Related Workmentioning

confidence: 99%

Rapid exploration with multi-rotors: A frontier selection method for high speed flight

Cieslewski

Kaufmann

Scaramuzza

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

187

165

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Abstract-Exploring and mapping previously unknown environments while avoiding collisions with obstacles is a fundamental task for autonomous robots. In scenarios where this needs to be done rapidly, multi-rotors are a good choice for the task, as they can cover ground at potentially very high velocities. Flying at high velocities, however, implies the ability to rapidly plan trajectories and to react to new information quickly. In this paper, we propose an extension to classical frontier-based exploration that facilitates exploration at high speeds. The extension consists of a reactive mode in which the multi-rotor rapidly selects a goal frontier from its field of view. The goal frontier is selected in a way that minimizes the change in velocity necessary to reach it. While this approach can increase the total path length, it significantly reduces the exploration time, since the multi-rotor can fly at consistently higher speeds. MULTIMEDIA MATERIALA video attachment to this work is available at https: //youtu.be/54s6gGZLpJo.

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Receding Horizon "Next-Best-View" Planner for 3D Exploration

Cited by 493 publications

References 22 publications

Survey on Computer Vision for UAVs: Current Developments and Trends

Survey on Computer Vision for UAVs: Current Developments and Trends

Multi-Camera Active-Vision for Markerless Shape Recovery of Unknown Deforming Objects

Rapid exploration with multi-rotors: A frontier selection method for high speed flight

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