Towards flapping wing robot visual perception: Opportunities and challenges

Eguíluz, A. Gómez; Paneque, J.L.; Grau, Pedro; Dios, J.R. Martínez-de; Ollero, A.

doi:10.1109/reduas47371.2019.8999674

Cited by 10 publications

(19 citation statements)

References 20 publications

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“…Finally, this work was developed in the context of the GRIFFIN ERC Advanced Grant, which objective is to develop autonomous flappingwing robotic systems capable of navigating, perching, and manipulating objects. The advantages of event cameras overcome some of the limitations of flapping-wing robot perception caused by agile maneuvers and abrupt movements [39]. Future work will also extend the proposed scheme to be used on board a flapping-wing robot to detect and track moving targets during perching and flight.…”

Section: Discussionmentioning

confidence: 99%

Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS

2021

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This paper presents an asynchronous event-based scheme for automatic intrusion monitoring using Unmanned Aerial Systems (UAS). Event cameras are neuromorphic sensors that capture the illumination changes in the camera pixels with high temporal resolution and dynamic range. In contrast to conventional frame-based cameras, they are naturally robust against motion blur and lighting conditions, which make them ideal for outdoor aerial robot applications. The presented scheme includes two main perception components. First, an asynchronous event-based processing system efficiently detects intrusions by combining several asynchronous event-based algorithms that exploit the advantages of the sequential nature of the event stream. The second is an off-line training mechanism that adjusts the parameters of the event-based algorithms to a particular surveillance scenario and mission. The proposed perception system was implemented in ROS for on-line execution on board UAS, integrated in an autonomous aerial robot architecture, and extensively validated in challenging scenarios with a wide variety of lighting conditions, including day and night experiments in pitch dark conditions.INDEX TERMS Event-based vision, intrusion detection, surveillance, UAV.

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Section: Discussionmentioning

confidence: 99%

Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS

2021

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“…Flapping-wing flight suffers from mechanical vibrations, and wide abrupt movements caused by the lift and thrust generated during downward strokes, which cause limitations in existing perception techniques [5]. Research in flappingwing robot perception is constrained by the high complexity of these platforms.…”

Section: This Work Has Been Developed Within the Griffin Ercmentioning

confidence: 99%

The GRIFFIN Perception Dataset: Bridging the Gap Between Flapping-Wing Flight and Robotic Perception

Tapia

Paneque

Grau

et al. 2021

IEEE Robot. Autom. Lett.

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The development of automatic perception systems and techniques for bio-inspired flapping-wing robots is severely hampered by the high technical complexity of these platforms and the installation of onboard sensors and electronics. Besides, flapping-wing robot perception suffers from high vibration levels and abrupt movements during flight, which cause motion blur and strong changes in lighting conditions. This paper presents a perception dataset for bird-scale flappingwing robots as a tool to help alleviate the aforementioned problems. The presented data include measurements from onboard sensors widely used in aerial robotics and suitable to deal with the perception challenges of flapping-wing robots, such as an event camera, a conventional camera, and two Inertial Measurement Units (IMUs), as well as ground truth measurements from a laser tracker or a motion capture system. A total of 21 datasets of different types of flights were collected in three different scenarios (one indoor and two outdoor). To the best of the authors' knowledge this is the first dataset for flapping-wing robot perception.

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“…The advantages of event cameras have motivated increasing research interest of the robotics and computer vision communities [3] [17]. A wide variety of methods have been used for feature extraction [18], clustering [19], tracking [20], optical flow computation [21], detect objects in motion [22], and SLAM [23], among many others.…”

Section: State Of the Artmentioning

confidence: 99%

Asynchronous Event-based Line Tracking for Time-to-Contact Maneuvers in UAS

Eguíluz

Dios

Ollero

2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents an bio-inspired event-based perception scheme for agile aerial robot maneuvering. It tries to mimic birds, which perform purposeful maneuvers by closing the separation in the retinal image (w.r.t. the goal) to follow time-to-contact trajectories. The proposed approach is based on event cameras, also called artificial retinas, which provide fast response and robustness against motion blur and lighting conditions. Our scheme guides the robot by only adjusting the position of features extracted in the event image plane to their goal positions at a predefined time using smooth timeto-contact trajectories. The proposed scheme is robust, efficient and can be added on top of commonly-used aerial robot velocity controllers. It has been validated on-board a UAV with real-time computation in low-cost hardware during sets of experiments with different descent maneuvers and lighting conditions.

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Towards flapping wing robot visual perception: Opportunities and challenges

Cited by 10 publications

References 20 publications

Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS

Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS

The GRIFFIN Perception Dataset: Bridging the Gap Between Flapping-Wing Flight and Robotic Perception

Asynchronous Event-based Line Tracking for Time-to-Contact Maneuvers in UAS

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