GNSS/LiDAR-Based Navigation of an Aerial Robot in Sparse Forests

Chiella, Antonio C. B.; Machado, Henrique N.; Teixeira, Bruno Otávio Soares; Pereira, Guilherme A. S.

doi:10.3390/s19194061

Cited by 26 publications

(20 citation statements)

References 33 publications

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“…This strategy generates control commands according to the detection of the events during flight and can be adopted in the delivery task. Still focusing on drone navigation with obstacle avoidance, the authors in Chiella et al (2019) present a localization approach and a vector field-based strategy for path following in sparse forests. They use GNSS and LiDAR data for location improvement and detection of trees, which are avoided using a probabilistic planner along with the vector field.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Navigation System for a Delivery Drone

Miranda

Rezende

Rocha

et al. 2021

J Control Autom Electr Syst

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The use of delivery services is an increasing trend worldwide, further enhanced by the COVID pandemic. In this context, drone delivery systems are of great interest as they may allow for faster and cheaper deliveries. This paper presented a navigation system that makes feasible the delivery of parcels with autonomous drones. The system generates a path between a start and a final point and controls the drone to follow this path based on its localization obtained through GPS, 9DoF IMU, and barometer. In the landing phase, information of poses estimated by a marker (ArUco) detection technique using a camera, ultrawideband (UWB) devices, and the drone’s software estimation are merged by utilizing an extended Kalman filter algorithm to improve the landing precision. A vector field-based method controls the drone to follow the desired path smoothly, reducing vibrations or harsh movements that could harm the transported parcel. Real experiments validate the delivery strategy and allow the evaluation of the performance of the adopted techniques. Preliminary results state the viability of our proposal for autonomous drone delivery.

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Section: Related Workmentioning

confidence: 99%

Autonomous Navigation System for a Delivery Drone

Miranda

Rezende

Rocha

et al. 2021

J Control Autom Electr Syst

View full text Add to dashboard Cite

show abstract

“…Autonomous navigation and automated tasks in forests are still a challenge due to the unstructured nature of such environment and to the unavailability and/or degradation of GNSS signals [2,3]. In [73], the authors claimed to solve such localisation problem in sparse forests, where the GNSS signals can be sporadically detected. They proposed a method that fuses GNSS information with a LiDAR-based odometry solution, which uses tree trunks as a feature input for a scan matching algorithm to estimate the relative movement of the aerial robot used in this work.…”

Section: Lidar Perceptionmentioning

confidence: 99%

Unimodal and Multimodal Perception for Forest Management: Review and Dataset

et al. 2021

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Robotics navigation and perception for forest management are challenging due to the existence of many obstacles to detect and avoid and the sharp illumination changes. Advanced perception systems are needed because they can enable the development of robotic and machinery solutions to accomplish a smarter, more precise, and sustainable forestry. This article presents a state-of-the-art review about unimodal and multimodal perception in forests, detailing the current developed work about perception using a single type of sensors (unimodal) and by combining data from different kinds of sensors (multimodal). This work also makes a comparison between existing perception datasets in the literature and presents a new multimodal dataset, composed by images and laser scanning data, as a contribution for this research field. Lastly, a critical analysis of the works collected is conducted by identifying strengths and research trends in this domain.

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“…For instance, a smart quadcopter aircraft navigation system using the global positioning system (GPS) was designed, which can achieve autonomous flight control with smooth and stable maneuvering, see Bonny & Abdelsalam (2019). Global navigation satellite systems (GNSS) intigrating light detection and ranging (LiDAR) scheme was investigated to achieve the autonomous navigation in forests (Chiella et al, 2019). The indoor quadrotor localization integrated by inertial navigation system (INS) and ultra wide band (UWB) was proposed by Xu et al (2020b).…”

Section: Introductionmentioning

confidence: 99%

Neural network assisted Kalman filter for INS/UWB integrated seamless quadrotor localization

Shen

et al. 2021

PeerJ Computer Science

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Due to some harsh indoor environments, the signal of the ultra wide band (UWB) may be lost, which makes the data fusion filter can not work. For overcoming this problem, the neural network (NN) assisted Kalman filter (KF) for fusing the UWB and the inertial navigation system (INS) data seamlessly is present in this work. In this approach, when the UWB data is available, both the UWB and the INS are able to provide the position information of the quadrotor, and thus, the KF is used to provide the localization information by the fusion of position difference between the INS and the UWB, meanwhile, the KF can provide the estimation of the INS position error, which is able to assist the NN to build the mapping between the state vector and the measurement vector off-line. The NN can estimate the KF’s measurement when the UWB data is unavailable. For confirming the effectiveness of the proposed method, one real test has been done. The test’s results demonstrate that the proposed NN assisted KF is effective to the fusion of INS and UWB data seamlessly, which shows obvious improvement of localization accuracy. Compared with the LS-SVM assisted KF, the proposed NN assisted KF is able to reduce the localization error by about 54.34%.

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GNSS/LiDAR-Based Navigation of an Aerial Robot in Sparse Forests

Cited by 26 publications

References 33 publications

Autonomous Navigation System for a Delivery Drone

Autonomous Navigation System for a Delivery Drone

Unimodal and Multimodal Perception for Forest Management: Review and Dataset

Neural network assisted Kalman filter for INS/UWB integrated seamless quadrotor localization

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