Journal: Autonomous Robots

Abbreviation

Auton. Robots

Publisher

Springer

Journal Volumes

ISSN

0929-5593
1573-7527

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Publications1 - 10 of 38
  • An informative path planning framework for UAV-based terrain monitoring
    Item type: Journal Article
    Popović, Marija; Vidal-Calleja, Teresa; Hitz, Gregory; et al. (2020)
    Autonomous Robots
    Unmanned aerial vehicles represent a new frontier in a wide range of monitoring and research applications. To fully leverage their potential, a key challenge is planning missions for efficient data acquisition in complex environments. To address this issue, this article introduces a general informative path planning framework for monitoring scenarios using an aerial robot, focusing on problems in which the value of sensor information is unevenly distributed in a target area and unknown a priori. The approach is capable of learning and focusing on regions of interest via adaptation to map either discrete or continuous variables on the terrain using variable-resolution data received from probabilistic sensors. During a mission, the terrain maps built online are used to plan information-rich trajectories in continuous 3-D space by optimizing initial solutions obtained by a coarse grid search. Extensive simulations show that our approach is more efficient than existing methods. We also demonstrate its real-time application on a photorealistic mapping scenario using a publicly available dataset and a proof of concept for an agricultural monitoring task.
  • AlphaPilot: autonomous drone racing
    Item type: Journal Article
    Foehn, Philipp; Brescianini, Dario; Kaufmann, Elia; et al. (2022)
    Autonomous Robots
    This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The system has successfully been deployed at the first autonomous drone racing world championship: the 2019 AlphaPilot Challenge. Contrary to traditional drone racing systems, which only detect the next gate, our approach makes use of any visible gate and takes advantage of multiple, simultaneous gate detections to compensate for drift in the state estimate and build a global map of the gates. The global map and drift-compensated state estimate allow the drone to navigate through the race course even when the gates are not immediately visible and further enable to plan a near time-optimal path through the race course in real time based on approximate drone dynamics. The proposed system has been demonstrated to successfully guide the drone through tight race courses reaching speeds up to 8m/s and ranked second at the 2019 AlphaPilot Challenge.
  • Adaptive fast open-loop maneuvers for quadrocopters
    Item type: Journal Article
    Lupashin, Sergei; D'Andrea, Raffaello (2012)
    Autonomous Robots
  • Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots
    Item type: Journal Article
    Bircher, Andreas; Kamel, Mina; Alexis, Kostas; et al. (2016)
    Autonomous Robots
  • Autonomous construction using scarce resources in unknown environments
    Item type: Journal Article
    Magnenat, Stéphane; Philippsen, Roland; Mondada, Francesco (2012)
    Autonomous Robots
    The goal of creating machines that autonomously perform useful work in a safe, robust and intelligent manner continues to motivate robotics research. Achieving this autonomy requires capabilities for understanding the environment, physically interacting with it, predicting the outcomes of actions and reasoning with this knowledge. Such intelligent physical interaction was at the centre of early robotic investigations and remains an open topic. In this paper, we build on the fruit of decades of research to explore further this question in the context of autonomous construction in unknown environments with scarce resources. Our scenario involves a miniature mobile robot that autonomously maps an environment and uses cubes to bridge ditches and build vertical structures according to high-level goals given by a human. Based on a “real but contrived” experimental design, our results encompass practical insights for future applications that also need to integrate complex behaviours under hardware constraints, and shed light on the broader question of the capabilities required for intelligent physical interaction with the real world.
  • Self-calibration and visual SLAM with a multi-camera system on a micro aerial vehicle
    Item type: Journal Article
    Heng, Lionel; Lee, Gim H.; Pollefeys, Marc (2015)
    Autonomous Robots
  • 3D multi-robot patrolling with a two-level coordination strategy
    Item type: Journal Article
    Freda, Luigi; Gianni, Mario; Pirri, Fiora; et al. (2019)
    Autonomous Robots
  • Chasing millimeters: design, navigation and state estimation for precise in-flight marking on ceilings
    Item type: Journal Article
    Lanegger, Christian; Pantic, Michael; Bähnemann, Rik; et al. (2023)
    Autonomous Robots
    Precise markings for drilling and assembly are crucial, laborious construction tasks. Aerial robots with suitable end-effectors are capable of markings at the millimeter scale. However, so far, they have only been demonstrated under laboratory conditions where rigid state estimation and navigation assumptions do not impede robustness and accuracy. This paper presents a complete aerial layouting system capable of precise markings on-site under realistic conditions. We use a compliant actuated end-effector on an omnidirectional flying base. Combining a two-stage factor-graph state estimator with a Riemannian Motion Policy-based navigation stack, we avoid the need for a globally consistent state estimate and increase robustness. The policy-based navigation is structured into individual behaviors in different state spaces. Through a comprehensive study, we show that the system creates highly precise markings at a relative precision of 1.5 mm and a global accuracy of 5-6 mm and discuss the results in the context of future construction robotics.
  • Optimal surveillance coverage for teams of micro aerial vehicles in GPS-denied environments using onboard vision
    Item type: Journal Article
    Doitsidis, Lefteris; Weiss, Stephan; Renzaglia, Alessandro; et al. (2012)
    Autonomous Robots
  • Distributed multi-robot formation control in dynamic environments
    Item type: Journal Article
    Alonso-Mora, Javier; Montijano, Eduardo; Nägeli, Tobias; et al. (2019)
    Autonomous Robots
    This paper presents a distributed method for formation control of a homogeneous team of aerial or ground mobile robots navigating in environments with static and dynamic obstacles. Each robot in the team has a finite communication and visibility radius and shares information with its neighbors to coordinate. Our approach leverages both constrained optimization and multi-robot consensus to compute the parameters of the multi-robot formation. This ensures that the robots make progress and avoid collisions with static and moving obstacles. In particular, via distributed consensus, the robots compute (a) the convex hull of the robot positions, (b) the desired direction of movement and (c) a large convex region embedded in the four dimensional position-time free space. The robots then compute, via sequential convex programming, the locally optimal parameters for the formation to remain within the convex neighborhood of the robots. The method allows for reconfiguration. Each robot then navigates towards its assigned position in the target collision-free formation via an individual controller that accounts for its dynamics. This approach is efficient and scalable with the number of robots. We present an extensive evaluation of the communication requirements and verify the method in simulations with up to sixteen quadrotors. Lastly, we present experiments with four real quadrotors flying in formation in an environment with one moving human.
Publications1 - 10 of 38