Minimum Snap Research Articles

HD Camera-Equipped UAV Trajectory Planning for Gantry Crane Inspection

While Unmanned Aerial Vehicles (UAVs) can be a valuable solution for the damage inspection of port machinery infrastructures, their trajectories are still prone to collision risks, trajectory non-smoothness, and large deviations. This research introduces a trajectory optimization method for inspecting vulnerable parts of a gantry crane by a UAV fitted with a high-definition (HD) camera. We first analyze the vulnerable parts of a gantry crane, then use the A* algorithm to plan a path for the UAV. The trajectory optimization process is divided into two steps, the first is a trajectory correction method and the second is an objective function that applies a minimum snap method while taking into consideration flight corridor constraints. The experimental simulation results show that, compared with previous methods, our approach can not only generate a collision-free and smooth trajectory but also shorten the trajectory length significantly while substantially reducing the maximum deviation average deviation distances. The simulation results show that this modelling approach provides a valuable solution for UAV trajectory planning for gantry crane inspection.

Quadrotor path planning using A* search algorithm and minimum snap trajectory generation

In this study, we propose a practical path planning method that combines the A* search algorithm and minimum snap trajectory generation. The A* search algorithm determines a set of waypoints to avoid collisions with surrounding obstacles from a starting to a destination point. Only essential waypoints (waypoints necessary to generate smooth trajectories) are extracted from the waypoints determined by the A* search algorithm, and an appropriate time between two adjacent waypoints is allocated. The waypoints so determined are connected by a smooth minimum snap trajectory, a dynamically executable trajectory for the quadrotor. If the generated trajectory is invalid, we methodically determine when intermediate waypoints are needed and how to insert the points to modify the trajectory. We verified the performance of the proposed method by various simulation experiments and a real-world experiment in a forested outdoor environment.

Study and Simulation of Autonomous Quadrotor Tracking a Pre-Defined Trajectory Using Matlab

The automated airborne vehicle (UAV) is an airplane that is worked without a human pilot. It was controlled either by the controller of a pilot or self-governingly by locally available PCs on the ground or in another vehicle. Modern Quadrotors are evolving than the old designs into a small agile vehicle. The quadrotor is increasingly becoming more and more popular, there is an increasing need for making this vehicle autonomous. The Methods for developing autonomous unmanned aerial vehicles has been an active area of research under the mobile platform. There are many commercially available drone platforms but all of them are required user interaction through a controller. In this work, we have created a control algorithm and trajectory generation for a smooth minimum snap trajectory through the given waypoints. Each waypoint specifies the desired position velocity, yaw, pitch, and roll angles. Such waypoints generated by our algorithm generate a smooth minimum snap trajectory between these waypoints. A PID controller is used to control the motions of the quadrotor in all planes.

Controlling Draft Interactions Between Quadcopter Unmanned Aerial Vehicles with Physics-aware Modeling

In this paper, we address the problem of multiple quadcopter control, where the quadcopters maneuver in close proximity resulting in interference due to air-drafts. We use sparse experimental data to estimate the interference area between palm sized quadcopters and to derive physics-infused models that describe how the air-draft generated by two quadcopters (flying one above the other) affect each other. The observed significant altitude deviations due to airdraft interactions, mainly in the lower quadcopter, is adequately captured by our physics infused machine learning model. We use two strategies to mitigate these effects. First, we propose non-invasive, online and offline trajectory re-planning strategies that allow avoiding the interference zone while reducing the deviations from desired minimum snap trajectories. Second, we propose invasive strategies that re-design control algorithms by incorporating the interference model. We demonstrate how to modify the standard quadcopter PID controller, and how to formulate a model predictive control approach when considering the interference model. Both invasive and non-invasive strategies show significant reduction in tracking error and control signal energy as compared to the case where the interference area is ignored.

UAV Trajectory Planning in a Port Environment

In many situations, the trajectory of an unmanned aerial vehicle (UAV) is very likely to deviate from the initial path generated by a path planning algorithm. This is in fact due to the existence of dynamic constraints of the UAV. In order to reduce the degree of such a deviation, this research introduces a trajectory planning algorithm, the objective of which is to minimize distance while maintaining security. The algorithm first develops preprocess trajectory points by constructing isosceles triangles then, on the basis of a minimum snap trajectory method, it applies a corridor constraint to an optimization objective function, while the deviation evaluation function is established to quantitatively evaluate the deviation distance. A series of experiments were carried out in a simulation environment with a simplified quay crane model. The results show that the proposed method not only optimizes the time and length of the generated trajectory, but also reduces the average deviation distance by 88.7%. Moreover, the generated trajectory can be well tracked by the UAV through qualitative and quantitative analysis. Overall, the experiments show that the proposed method can generate a higher UAV trajectory quality.

Autonomous Load Control and Transportation Using Multiple Quadrotors

This paper discusses the development of a generalized framework for collaborative control and transportation of a suspended load using multiple quadrotors. For this, first, a flight dynamics model of quadrotors with suspended load system is derived using Newton’s approach. Next, a cooperative control law is developed to control the motion of the quadrotor(s) and the suspended load. The vehicle formation ensures that the load distribution among vehicles remains equal throughout the transportation task. The proposed control approach uses the combination of a proportional–integral derivative (PID) and a proportional derivative (PD) controller for position control and transportation. The PID controller controls the motion of quadrotor, whereas the PD controller controls the swing, maintains the formation of quadrotors, and simultaneously damps the oscillation of the load. The combination facilitates the waypoint transition and trajectory tracking of the load. A minimum snap trajectory generation approach for the suspended load is also presented. The performance is demonstrated in a simulation as well as experimentally on a single and multiple quadrotors in three-dimensional environment using the motion capture system. The experimental result for a single-lift system is also presented for the outdoor environment.

A Visual Interface Tool for Development of Quadrotor Control Strategies

Quadrotor control is an exciting research area due to its inherent non-linearity, the variety of tasks to be performed, and the wide scope of control strategies. Despite several works have been published, some aspects must be considered before implementation: How a quadrotor will operate in challenging trajectories, how to define trajectory limits, or how changing the device size will affect its performance. A complete user-friendly development platform is presented, where any device may be tested just by setting a few parameters. Typing a set of waypoints and their corresponding times, the tool calculates the optimal trajectory with minimum snap. For the defined waypoints, the control gains are tuned for a chosen control strategy using Particle Swarm Optimization (PSO). Three control strategies are available, but the tool was developed in modular form and opened to others. After tuned the gains the control performance may be visually evaluated through a graphical user interface (GUI). The quadrotor model considers the effect of air drag and propellers’ speed dynamics. Measurement noise and limits for propeller speeds were also considered. Results demonstrate how this tool helps to initiate undergraduate and beginner graduate students in this research area, testing new control strategies, defining limits in challenging trajectories, and determining quadrotor characteristics for specific applications. The tool is available in GitHub (Martins and Rendon 2019).

Centralized Control System Design for Underwater Transportation using two Hovering Autonomous Underwater Vehicles (HAUVs)

Abstract In this paper, a centralized control system is designed for the two HAUVs undertaking underwater transportation of a spherical payload via cylindrical manipulators. First, the nonlinear coupled dynamic model is developed considering the rigid body connection method for transportation. The effect of the hydrodynamic, hydrostatic and thrust parameters are taken about the centre of the combined body i.e. the centre of payload. Path trajectory is generated using the minimum snap trajectory algorithm. The trajectory is divided into segments for each directional motion which is further divided into the waypoints based on the time step of the duration. The path between two waypoints is represented by a 7th order polynomial. The centralized control system is designed to follow the desired trajectory. The control system is designed using PID controllers for the motion control in each direction. The main technical requirements are the stability of the payload, accurate trajectory tracking and robustness to overcome uncertainties. Stability cannot be compromised because of the rigid connection between the vehicles and the payload, whereas, tracking is given a tolerance of ±5%. Transportation task is observed for the desired motion in the horizontal plane. The time domain motion simulation results show that the desired trajectory has been accurately followed by the combined system while meeting the technical requirements.

Type-2 Fuzzy Logic Trajectory Tracking Control of Quadrotor VTOL Aircraft With Elliptic Membership Functions

Emerging applications of quadrotor vertical take-off and landing (VTOL) unmanned aerial vehicles in various fields have created a need for demanding controllers that are able to counter several challenges, inter alia, nonlinearity, underactuated dynamics, lack of modeling, and uncertainties in the working environment. This study compares and contrasts type-1 and type-2 fuzzy neural networks (T2FNNs) for the trajectory tracking problem of quadrotor VTOL aircraft in terms of their tracking accuracy and control efforts. A realistic trajectory consisting of both straight lines and curvatures for a surveillance operation with minimum snap property, which is feasible regarding input constraints of the quadrotor, is generated to evaluate the proposed controllers. In order to imitate the outdoor noisy and time-varying working conditions, realistic uncertainties, such as wind and gust disturbances, are fed to the real-time experiment in the laboratory environment. Furthermore, a cost function based on the integral of the square of the sliding surface, which gives the optimal parameter update rules, is used to train the consequent part parameters of the T2FNN. Thanks to the learning capability of the proposed controllers, experimental results show the efficiency and efficacy of the learning algorithms that the proposed T2FNN-based controller with the optimal tuning algorithm is 50% superior to a conventional proportional-derivative (PD) controller in terms of control accuracy but requires more control effort. T2FNN structures are also shown to possess better noise reduction property as compared to their type-1 counterparts in the presence of unmodeled noise and disturbances.

Total dietary fibre and antioxidant activity of gluten free cookies made from raw and germinated amaranth (Amaranthus spp.) flour

Gluten free cookies were prepared from raw and germinated amaranth grain flour. The chemical, functional and pasting properties of raw and germinated amaranth flour were studied. Germination decreased fat from 6.68 g to 4.7 g/100 g and carbohydrate 62.41 g–60.70 g/100 g while an increase was noticed in protein from 15.05 g to 16.5 g/100 g, total dietary fibre from 9.52 g to 12.9 g/100 g and antioxidant activity from 10.23 g to 14.71 g/100 g, respectively. Further, functional properties were improved on germination. Pasting properties values were decreased with germination. The gluten-free cookies were evaluated for their physical, textural, colour, antioxidant activity, total dietary fibre and sensory attributes. Raw amaranth flour cookies showed the highest spread ratio, followed by germinated amaranth flour and wheat flour cookies. Germinated amaranth flour cookies require minimum snap force. Germinated amaranth cookies exhibited highest antioxidant activity (21.43 g/100 g) and total dietary fibre (13.97 g/100 g) as compared to raw amaranth and wheat flour cookies. The overall results showed that the cookies with acceptable quality and improved nutrition could be prepared from germinated amaranth flour.