A method for UAV multi-sensor fusion 3D-localization under degraded or denied GPS situation

2018 ◽  
Vol 6 (3) ◽  
pp. 155-176 ◽  
Author(s):  
Thanabadee Bulunseechart ◽  
Pruittikorn Smithmaitrie
Keyword(s):  
Position Estimation ◽  
Measurement Unit ◽  
Sensor Calibration ◽  
Complex Environments ◽  
Indicator Method ◽  
3D Localization ◽  
Gps Measurement ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Optical Flow Sensor

Unmanned aerial vehicles (UAVs) have been developed to be used in complex environments. Continuity of a UAV operation when GPS is degraded or denied is crucial in many applications, such as flying near high buildings and trees, or flying outdoor-to-indoor. In this paper, an algorithm for 3D-localization during transition between indoor and outdoor environments for a UAV is presented. Localization inputs are based on information from GPS, inertial measurement unit, monocular camera, and optical flow sensor. Information is carefully selected using GPS quality indicator method corresponding to the operating environment. After that, a smoothing offset approach is employed to smooth the position estimation. The selected sensors’ data are filtered by indirect extended Kalman filter for localization and extrinsic sensor calibration in real time. Results show a seamless offset convergence of UAV localization for indoor–outdoor transition. Moreover, the proposed method of decision-making to cut off GPS measurement even when it experiences poor signal quality can still outperform conventional GPS-based cutoff method in terms of response time.

scholarly journals VIMO: A Visual-Inertial-Magnetic Navigation System Based on Non-Linear Optimization

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4386
Author(s):  
Jingzhe Wang ◽  
Leilei Li ◽  
Huan Yu ◽  
Xunya Gui ◽  
Zucheng Li
Keyword(s):  
Large Scale ◽  
Linear Optimization ◽  
Position Estimation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Non Linear ◽  
Outdoor Environments ◽  
Novel Method ◽  
And Performance ◽  
Inertial Measurements

Visual-inertial navigation systems are credited with superiority over both pure visual approaches and filtering ones. In spite of the high precision many state-of-the-art schemes have attained, yaw remains unobservable in those systems all the same. More accurate yaw estimation not only means more accurate attitude calculation but also leads to better position estimation. This paper presents a novel scheme that combines visual and inertial measurements as well as magnetic information for suppressing deviation in yaw. A novel method for initializing visual-inertial-magnetic odometers, which recovers the directions of magnetic north and gravity, the visual scalar factor, inertial measurement unit (IMU) biases etc., has been conceived, implemented, and validated. Based on non-linear optimization, a magnetometer cost function is incorporated into the overall optimization objective function as a yawing constraint among others. We have done extensive research and collected several datasets recorded in large-scale outdoor environments to certify the proposed system’s viability, robustness, and performance. Cogent experiments and quantitative comparisons corroborate the merits of the proposed scheme and the desired effect of the involvement of magnetic information on the overall performance.

Riding Motion Capture System Using Inertial Measurement Units with Contact Constraints

2019 ◽  
Vol 13 (4) ◽  
pp. 506-516 ◽  
Author(s):  
Tsubasa Maruyama ◽  
Mitsunori Tada ◽  
Haruki Toda ◽  
◽  
Keyword(s):  
Motion Capture ◽  
Bicycle Ergometer ◽  
Human Motion ◽  
Position Estimation ◽  
Estimation Accuracy ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Outdoor Environments ◽  
Optical Motion ◽  
Optical Motion Capture

The measurement of human motion is an important aspect of ergonomic mobility design, in which the mobility product is evaluated based on human factors obtained by digital human (DH) technologies. The optical motion-capture (MoCap) system has been widely used for measuring human motion in laboratories. However, it is generally difficult to measure human motion using mobility products in real-world scenarios, e.g., riding a bicycle on an outdoor slope, owing to unstable lighting conditions and camera arrangements. On the other hand, the inertial-measurement-unit (IMU)-based MoCap system does not require any optical devices, providing the potential for measuring riding motion even in outdoor environments. However, in general, the estimated motion is not necessarily accurate as there are many errors due to the nature of the IMU itself, such as drift and calibration errors. Thus, it is infeasible to apply the IMU-based system to riding motion estimation. In this study, we develop a new riding MoCap system using IMUs. The proposed system estimates product and human riding motions by combining the IMU orientation with contact constraints between the product and DH, e.g., DH hands in contact with handles. The proposed system is demonstrated with a bicycle ergometer, including the handles, seat, backrest, and foot pedals, as in general mobility products. The proposed system is further validated by comparing the estimated joint angles and positions with those of the optical MoCap for three different subjects. The experiment reveals both the effectiveness and limitations of the proposed system. It is confirmed that the proposed system improves the joint position estimation accuracy compared with a system using only IMUs. The angle estimation accuracy is also improved for near joints. However, it is observed that the angle accuracy decreases for a few joints. This is explained by the fact that the proposed system modifies the orientations of all body segments to satisfy the contact constraints, even if the orientations of a few joints are correct. This further confirms that the elapsed time using the proposed system is sufficient for real-time application.

Accurate 3D Localization Using RGB-TOF Camera and IMU for Industrial Mobile Robots

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Majid Yekkehfallah ◽  
Ming Yang ◽  
Zhiao Cai ◽  
Liang Li ◽  
Chuanxiang Wang
Keyword(s):  
Mobile Robots ◽  
Inertial Measurement Unit ◽  
Indoor Environment ◽  
State Of The Art ◽  
Low Cost ◽  
Estimation Algorithm ◽  
Measurement Unit ◽  
3D Localization ◽  
Fast Motion ◽  
Tof Camera

SUMMARY Localization based on visual natural landmarks is one of the state-of-the-art localization methods for automated vehicles that is, however, limited in fast motion and low-texture environments, which can lead to failure. This paper proposes an approach to solve these limitations with an extended Kalman filter (EKF) based on a state estimation algorithm that fuses information from a low-cost MEMS Inertial Measurement Unit and a Time-of-Flight camera. We demonstrate our results in an indoor environment. We show that the proposed approach does not require any global reflective landmark for localization and is fast, accurate, and easy to use with mobile robots.

Impacts of Different Winter Storage Conditions on the Physiology of Diutinus Honey Bees (Hymenoptera: Apidae)

2021 ◽  
Author(s):  
Brandon K Hopkins ◽  
Priyadarshini Chakrabarti ◽  
Hannah M Lucas ◽  
Ramesh R Sagili ◽  
Walter S Sheppard
Keyword(s):  
Honey Bees ◽  
The United States ◽  
Storage Conditions ◽  
Colony Losses ◽  
Bee Colony ◽  
Causative Factors ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Physiological Markers ◽  
Honey Bee Colony Losses

Abstract Global decline in insect pollinators, especially bees, have resulted in extensive research into understanding the various causative factors and formulating mitigative strategies. For commercial beekeepers in the United States, overwintering honey bee colony losses are significant, requiring tactics to overwinter bees in conditions designed to minimize such losses. This is especially important as overwintered honey bees are responsible for colony expansion each spring, and overwintered bees must survive in sufficient numbers to nurse the spring brood and forage until the new ‘replacement’ workers become fully functional. In this study, we examined the physiology of overwintered (diutinus) bees following various overwintering storage conditions. Important physiological markers, i.e., head proteins and abdominal lipid contents were higher in honey bees that overwintered in controlled indoor storage facilities, compared with bees held outdoors through the winter months. Our findings provide new insights into the physiology of honey bees overwintered in indoor and outdoor environments and have implications for improved beekeeping management.

scholarly journals A Hybrid Framework for Mitigating Heading Drift for a Wearable Pedestrian Navigation System through Adaptive Fusion of Inertial and Magnetic Measurements

2021 ◽  
Vol 11 (4) ◽  
pp. 1902
Author(s):  
Liqiang Zhang ◽  
Yu Liu ◽  
Jinglin Sun
Keyword(s):  
Magnetic Measurements ◽  
Inertial Sensor ◽  
Angular Rate ◽  
Human Motion ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
Hybrid Framework ◽  
Outdoor Environments ◽  
Adaptive Fusion ◽  
Indoor And Outdoor Environments

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift.

scholarly journals Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

2021 ◽  
Author(s):  
Yue Zhao ◽  
Feng Gao ◽  
Qiao Sun ◽  
Yunpeng Yin
Keyword(s):  
Legged Robots ◽  
Measurement Unit ◽  
Support Vector ◽  
Hexapod Robot ◽  
Terrain Classification ◽  
Adaptive Locomotion ◽  
Joint Torques ◽  
Active Compliance ◽  
Outdoor Environments ◽  
The Stability

AbstractLegged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

scholarly journals Health Effects and Exposure Assessment to Bioaerosols in Indoor and Outdoor Environments

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 359
Author(s):  
Ewa Brągoszewska
Keyword(s):  
Exposure Assessment ◽  
Health Effects ◽  
Special Issue ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

The Atmosphere Special Issue entitled “Health Effects and Exposure Assessment to Bioaerosols in Indoor and Outdoor Environments” comprises five original papers [...]

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