This article proposes a Rao-Blackwellized particle filter (RBPF) for fully mixing state-space models that replace the Kalman filter within the RBPF method with a noise-adaptive Kalman filter. This ...extension aims to deal with unknown time-varying measurement variances. Consequently, a variational Bayesian (VB) adaptive Kalman filter estimates the conditionally linear states and the measurement noise variances whereas the nonlinear (or latent) states are handled by sequential Monte Carlo (MC) sampling. Thus, by modifying the underlying mathematical framework of RBPF, we construct the Monte Carlo Variational Bayesian (MCVB) filter. A stopping criterion for VB approximations is proposed by employing Tikhonov regularization. Additionally, an analysis of the numerical stability of the proposed filtering mechanism is presented. The performance of the MCVB filter is illustrated in simulations and mobile robot tracking experiments in the presence of measurement model uncertainties.
A priori knowledge about the height profile of the path is vital for rollover avoidance in the context of autonomous driving through uneven forest ground. The forest ground is usually covered with ...either soft vegetation in summertime, or by snow in winter. Thus, the exact solid form of the forest ground cannot be detected by camera or LiDAR. This article, we propose height-odometry and aided height-odometry methods for ground height estimation. The height-odometry method depends solely on interoceptive and proprioceptive sensor data, while the aided height-odometry combines height-odometry output with the existing 3D map information. Thus, the central idea is to build a reference 3D path for autonomous forest machines where the spatial positioning – based on the RTK-GNSS or Forest SLAM method – is fused with the output of (aided) height-odometry method(s). We evaluate the proposed height-odometry methods in two separate environments that are accurately (3D) mapped by a UAV using the advanced machine-vision-based SfM method and the LiDAR-based SLAM algorithms. Through comprehensive data analysis, we demonstrate that the proposed 3D path estimation methods are practical and simple to implement, yet sufficient to estimate the height profile of the path with desired accuracy.
•A priori knowledge of the ground’s elevation profile is crucial for autonomous harvesting operations.•The height-odometry and aided height-odometry methods are introduced to compute the ground’s elevation profile.•Our methods rely on the vehicle’s geometry, IMU data, wheel height measurement, and a sparse a priori 3D map.•The reference elevation models are created using sophisticated methods involving drone mapping.•The performance of the proposed height estimation methods is evaluated against reference methods in both open and covered areas.
Display omitted
3D path estimation, i.e., determining the height profiles of the path, is crucial in motion control for autonomous driving in terrains. It is essential to prevent rollover from abrupt peaks, dips, ...and briefly wet ground. In this study, wheel displacement measurements and height estimation of an off-road vehicle are presented. A calibration process is suggested to measure the instantaneous vertical displacement of each wheel. GNSS-pose-based methods are used to estimate the vehicle's geometry parameters yielding the centimeter-level accuracy of the 3D-path estimation method. The accuracy of the vehicle's instrumentation is examined on a test track to create a 3D terrain model of the path. The outcome of the proposed scheme is compared to a reference elevation profile created with structure from motion on the basis of machine vision and GNSS using data collected by an unmanned aerial vehicle. The comparison of the results demonstrates that the 3D path can be estimated with sufficient accuracy in open terrain using ground vehicles.
This study highlights a combined center of gravity (CG) approach to model the comprehensive dynamics of the ground vehicles with articulated steering using solely six degrees of freedom (6-DOF). It ...is the case with an articulated vehicle that its CG shifts laterally towards the center of rotation during a turn. Thus, the idea is to compute the combined CG position of the multi-body articulated vehicle, which leads to the correction of the moment arms and body inertias about the updated CG position in the dynamic equations. Hence, the body forces and moments are computed with respect to the corrected CG position. In addition, the paper illustrates mathematical modeling of the center-articulated steering mechanism for the ground vehicle while restricting its operation to the primary handling regime. Overall, the draft presents the design of a nonlinear 6-DOF simulation for a load-haul-dump (LHD) type of articulated vehicle with a traveling CG. The simulation data is presented from one simulation run, where the critical results are analyzed. The obtained results signify the simplicity in using a combined CG to represent the vehicle dynamics.
The automobile industry usually ignores the height of the path and uses planar vehicle models to implement automatic vehicle control. In addition, existing literature mostly concerns level terrain or ...homogeneous road surfaces for estimating vehicle dynamics. However, ground vehicles utilized in forestry, such as forwarders, operate on uneven terrain. The vehicle models built on level terrain assumptions are inadequate to capture the rolling or pitching dynamics of such machines as rollover of such vehicles is a potential risk. Therefore, knowledge about the height profile of the path is crucial for automating such off-road operations and avoiding rollover. We propose the use of a six-degrees-of-freedom (6-DOF) dynamic vehicle model to solve the autonomous forwarder problem. An adaptive linear tire model is used in the 6-DOF model assuming the vehicle operates in a primary handling regime. The force models are modified to include the three-dimensional (3D) map information. The calibration procedures, identifying actuator dynamics, and quantifying sensor delays are also represented.
The proposed vehicle modeling contributed to realizing the continuous-discrete extended Kalman filter (CDEKF), which takes into account the 3D path during filtering and fixed-lag smoothing. Polaris (an all-terrain electric car) is used as a case study to experimentally validate the vehicle modeling and performance of the state estimator. Three types of grounds are selected – an asphalt track, a concrete track with a high elevation gradient, and a gravel track inside a forest. Stable state estimates are obtained using CDEKF and sparse 3D maps of terrains despite discontinuities in satellite navigation data inside the forest. The height estimation results are obtained with sufficient accuracy when compared to ground truth obtained by aerial 3D mapping. Finally, the proposed model’s applicability for predictive control is demonstrated by utilizing the state estimates to predict future states considering (3D) terrain.
•Prior knowledge about the height profile of the path is crucial for automating forest machine chain operations and avoiding rollover.•A six-degrees-of-freedom (6-DOF) dynamic vehicle model is used to solve the autonomous forwarder problem.•The calibration procedures, identifying actuator dynamics, and quantifying sensor delays are also represented.•Stable state estimates are obtained using continuous-discrete extended Kalman filter (CDEKF) and sparse 3D terrain maps despite satellite navigation data discontinuities.•The applicability of the proposed vehicle dynamic modeling for predictive control is demonstrated.
The requirement of a robust, recursive online parameter estimation for real-time identification of faults in UAVs during autonomous flights is increasing. This paper presents a recursive algorithm ...for estimation of thrust and power coefficients of a propeller-engine driven fixed wing UAV. Extended Kalman Filter with a high fidelity nonlinear 6-DOF model of the UAV is used to estimate a linear fit for the thrust and power coefficients at the current operating point. Minimal sensor suit normally used in the autonomous flight of the UAV is used as the basis of available measurements. High fidelity nonlinear simulations are used to verify the effectiveness of the algorithm in a simulated flight and results are presented.
This paper presents a method for fusing the control inputs of the external manual pilot with the autopilot commands to enhance the manual flight safety of UAVs (Unmanned Aerial Vehicles). The fusion ...restricts the pilot from taking the UAV into unrecoverable flight regimes by limiting the roll angles to certain limits while allowing full control authority if the UAV remains inside the limits. Outside the limits the robust adaptive autonomous control ensures the stability of the system. The scheme was tested in a high fidelity nonlinear hardware in the loop simulation for the King Saud University testbed UAV to show the effectiveness of the scheme.
Cancer is one of the leading causes of death worldwide. A slight decline in mortality has been noted, but the currently available treatment options did not give an expected outcome and are associated ...with several side effects resulting a substantial economic burden. The advent of plant-based treatment is rising because of its ease of use, ready availability, cost-effectiveness, and low/no toxicity. In recent years, flavonoids with their diverse physico-biological properties have gained the scientific community's attention for the treatment of various forms of cancer. Different flavonoids, especially, flavonols (quercetin, kaempferol, fisetin, and isorhamnetin), flavanones (hesperidin and naringin), and anthocyanins, have shown potent anticancer activities affecting various signaling cascades. Among those, phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt)/ mammalian target of rapamycin (mTOR) signaling pathway is widely known to play a significant role in different physio-cellular activities, which triggers malignant transformation and is considered a key target for anticancer compounds. This pathway plays a vital role in regulating the cell cycle, metabolism, survival, and proliferation. The flavonoids exhibit their anticancer activity via different molecular pathways, including PI3K/Akt/mTOR. In the current piece of paper, our focus is to underpin the action of the above-mentioned flavonoids against different cancers, mainly covering in-vitro data, through PI3K/Akt/mTOR targeting.
Salicylic acid (SA) is a well-known plant growth regulator, which participates in many physiological processes of plants under normal and stressful conditions. In this study, we investigated the ...impact of SA supplementation on the components of ascorbate-glutathione cycle and glyoxalase system, photosynthesis and growth of rice (Oryza sativa) plants subjected to arsenic (As) stress. Plants grown with As exhibited enhanced As uptake, increased oxidative stress, and photosynthesis and growth inhibition. Application of SA promoted photosynthesis and growth in plants with or without As stress by improving plant defense systems and reducing oxidative stress through interaction with ethylene and nitric oxide (NO). SA acted as an ethylene antagonist, reducing stress ethylene formation under As stress, while NO formation was induced. This resulted in coordinated control over the antioxidant defense systems and enhanced As tolerance, protecting photosynthesis and growth from As-induced damage. The study showed that positive responses of SA in promoting photosynthesis and growth under As stress were the result of its interplay with ethylene and NO, enhanced capacity of defense systems to reduce oxidative stress. The crosstalk of SA with ethylene and NO will be useful in augmenting the performance of rice plants under As stress.
•Arsenic stress increases oxidative stress and inhibits photosynthesis.•Salicylic acid strengthens defense mechanisms under As stress.•Salicylic acid improves photosynthesis and growth under As stress.•Salicylic acid interacts with ethylene and nitric oxide for As tolerance.
PDF
