scholarly journals Online Trajectory Planning Method for Double-Pendulum Quadrotor Transportation Systems

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Juntong Qi ◽  
Yuan Ping ◽  
Mingming Wang ◽  
Chong Wu
Keyword(s):  
Trajectory Planning ◽  
Transportation Systems ◽  
Planning Method ◽  
Stability And Convergence ◽  
Planning Problem ◽  
Double Pendulum ◽  
Precise Positioning ◽  
Excellent Control ◽  
The Stability ◽  
Invariance Theory

This study investigates the trajectory planning problem for double-pendulum quadrotor transportation systems. The goal is to restrain the hook swing and payload swing while achieving precise positioning. An online trajectory planning method with two capabilities—precise positioning and swing suppression—is proposed. The stability and convergence of the system are proved using the Lyapunov principle and the LaSalle’s invariance theory. Simulation results show that the proposed method has excellent control performance.

scholarly journals Online trajectory planning for UCAV performing ground attacks based on threat modeling

2021 ◽  
Vol 39 (2) ◽  
pp. 382-391
Author(s):  
Jiayu Tang ◽  
Xiangmin Li ◽  
Jinjin Dai
Keyword(s):  
Trajectory Planning ◽  
Aerodynamic Characteristics ◽  
Planning Method ◽  
Planning Problem ◽  
Threat Modeling ◽  
Performance Constraints ◽  
Engine Thrust ◽  
Online Planning ◽  
Aerial Vehicle ◽  
Kinematic Models

The paper studies how to plan the trajectories of an unmanned combat aerial vehicle (UCAV) that releases its airborne weapons and presents an online trajectory planning method based on threat modeling. Firstly, it analyzes the aerodynamic characteristics, engine thrust and fuel characteristics of the UCAV and builds its dynamic and kinematic models. Secondly, the trajectory planning model of the UCAV is formulated with flight performance constraints and battlefield threat constraints considered. To improve the accuracy of ground attacks, the envelope of a guided bomb's acceptable region of weapon release is studied, and the release center and posture of the guided bomb work as terminal planning conditions. Thirdly, an online trajectory planning method is proposed. With the help of threat modeling, the complicated trajectory planning problem is transformed into a simplified situation classification. Finally, the simulation results demonstrate that the online planning method proposed in the paper can provide feasible trajectories for a UCAV to succeed in releasing its airborne weapons.

scholarly journals A Trajectory Planning Method for Autonomous Valet Parking via Solving an Optimal Control Problem

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6435
Author(s):  
Chen Chen ◽  
Bing Wu ◽  
Liang Xuan ◽  
Jian Chen ◽  
Tianxiang Wang ◽  
...  
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Trajectory Planning ◽  
Pseudospectral Method ◽  
Initial Guess ◽  
Planning Method ◽  
Planning Problem ◽  
Starting Position ◽  
Dynamic Obstacle Avoidance

In the last decade, research studies on parking planning mainly focused on path planning rather than trajectory planning. The results of trajectory planning are more instructive for a practical parking process. Therefore, this paper proposes a trajectory planning method in which the optimal autonomous valet parking (AVP) trajectory is obtained by solving an optimal control problem. Additionally, a vehicle kinematics model is established with the consideration of dynamic obstacle avoidance and terminal constraints. Then the parking trajectory planning problem is modeled as an optimal control problem, while the parking time and driving distance are set as the cost function. The homotopic method is used for the expansion of obstacle boundaries, and the Gauss pseudospectral method (GPM) is utilized to discretize this optimal control problem into a nonlinear programming (NLP) problem. In order to solve this NLP problem, sequential quadratic programming is applied. Considering that the GPM is insensitive to the initial guess, an online calculation method of vertical parking trajectory is proposed. In this approach, the offline vertical parking trajectory, which is calculated and stored in advance, is taken as the initial guess of the online calculation. The selection of an appropriate initial guess is based on the actual starting position of parking. A small parking lot is selected as the verification scenario of the AVP. In the validation of the algorithm, the parking trajectory planning is divided into two phases, which are simulated and analyzed. Simulation results show that the proposed algorithm is efficient in solving a parking trajectory planning problem. The online calculation time of the vertical parking trajectory is less than 2 s, which meets the real-time requirement.

scholarly journals Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1250
Author(s):  
Daniel Medina ◽  
Haoqing Li ◽  
Jordi Vilà-Valls ◽  
Pau Closas
Keyword(s):  
Intelligent Transportation Systems ◽  
Robust Statistics ◽  
Real Data ◽  
Transportation Systems ◽  
Global Navigation Satellite Systems ◽  
Mixed Integer ◽  
Robust Filtering ◽  
Precise Positioning ◽  
The Impact ◽  
Filtering Techniques

Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

scholarly journals Stability-Guaranteed and High Terrain Adaptability Static Gait for Quadruped Robots

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4911
Author(s):  
Qian Hao ◽  
Zhaoba Wang ◽  
Junzheng Wang ◽  
Guangrong Chen
Keyword(s):  
Impedance Control ◽  
Stability Margin ◽  
Planning Method ◽  
Legged Robots ◽  
Gait Planning ◽  
Quadruped Locomotion ◽  
Quadruped Robots ◽  
Adjustment Strategy ◽  
Compliant Behavior ◽  
The Stability

Stability is a prerequisite for legged robots to execute tasks and traverse rough terrains. To guarantee the stability of quadruped locomotion and improve the terrain adaptability of quadruped robots, a stability-guaranteed and high terrain adaptability static gait for quadruped robots is addressed. Firstly, three chosen stability-guaranteed static gaits: intermittent gait 1&2 and coordinated gait are investigated. In addition, then the static gait: intermittent gait 1, which is with the biggest stability margin, is chosen to do a further research about quadruped robots walking on rough terrains. Secondly, a position/force based impedance control is employed to achieve a compliant behavior of quadruped robots on rough terrains. Thirdly, an exploratory gait planning method on uneven terrains with touch sensing and an attitude-position adjustment strategy with terrain estimation are proposed to improve the terrain adaptability of quadruped robots. Finally, the proposed methods are validated by simulations.

scholarly journals Numerical simulation of periodic MHD casson nanofluid flow through porous stretching sheet

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Abdullah Al-Mamun ◽  
S. M. Arifuzzaman ◽  
Sk. Reza-E-Rabbi ◽  
Umme Sara Alam ◽  
Saiful Islam ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Lewis Number ◽  
Stability And Convergence ◽  
Radiation Absorption ◽  
Physical Parameters ◽  
Theoretical Idea ◽  
Prostate Cancer Therapy ◽  
Flow Through ◽  
Explicit Finite Difference ◽  
The Stability

AbstractThe perspective of this paper is to characterize a Casson type of Non-Newtonian fluid flow through heat as well as mass conduction towards a stretching surface with thermophoresis and radiation absorption impacts in association with periodic hydromagnetic effect. Here heat absorption is also integrated with the heat absorbing parameter. A time dependent fundamental set of equations, i.e. momentum, energy and concentration have been established to discuss the fluid flow system. Explicit finite difference technique is occupied here by executing a procedure in Compaq Visual Fortran 6.6a to elucidate the mathematical model of liquid flow. The stability and convergence inspection has been accomplished. It has observed that the present work converged at, Pr ≥ 0.447 indicates the value of Prandtl number and Le ≥ 0.163 indicates the value of Lewis number. Impact of useful physical parameters has been illustrated graphically on various flow fields. It has inspected that the periodic magnetic field has helped to increase the interaction of the nanoparticles in the velocity field significantly. The field has been depicted in a vibrating form which is also done newly in this work. Subsequently, the Lorentz force has also represented a great impact in the updated visualization (streamlines and isotherms) of the flow field. The respective fields appeared with more wave for the larger values of magnetic parameter. These results help to visualize a theoretical idea of the effect of modern electromagnetic induction use in industry instead of traditional energy sources. Moreover, it has a great application in lung and prostate cancer therapy.

scholarly journals Trajectory Planning Method for Mixed Vehicles Considering Traffic Stability and Fuel Consumption at the Signalized Intersection

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shan Fang ◽  
Lan Yang ◽  
Tianqi Wang ◽  
Shoucai Jing
Keyword(s):  
Fuel Consumption ◽  
Trajectory Planning ◽  
Signalized Intersections ◽  
Planning Method ◽  
Signalized Intersection ◽  
Driver Model ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Traffic Lights ◽  
Trigonometric Model

Traffic lights force vehicles to stop frequently at signalized intersections, which leads to excessive fuel consumption, higher emissions, and travel delays. To address these issues, this study develops a trajectory planning method for mixed vehicles at signalized intersections. First, we use the intelligent driver car-following model to analyze the string stability of traffic flow upstream of the intersection. Second, we propose a mixed-vehicle trajectory planning method based on a trigonometric model that considers prefixed traffic signals. The proposed method employs the proportional-integral-derivative (PID) model controller to simulate the trajectory when connected vehicles (equipped with internet access) follow the optimal advisory speed. Essentially, only connected vehicle trajectories need to be controlled because normal vehicles simply follow the connected vehicles according to the Intelligent Driver Model (IDM). The IDM model aims to minimize traffic oscillation and ensure that all vehicles pass the signalized intersection without stopping. The results of a MATLAB simulation indicate that the proposed method can reduce fuel consumption and NOx, HC, CO2, and CO concentrations by 17%, 22.8%, 17.8%, 17%, and 16.9% respectively when the connected vehicle market penetration is 50 percent.

scholarly journals A New Methodology for Solving Trajectory Planning and Dynamic Load-Carrying Capacity of a Robot Manipulator

2016 ◽  
Vol 2016 ◽  
pp. 1-28 ◽  
Author(s):  
Wanjin Guo ◽  
Ruifeng Li ◽  
Chuqing Cao ◽  
Xunwei Tong ◽  
Yunfeng Gao
Keyword(s):  
Trajectory Planning ◽  
Dynamic Load ◽  
Carrying Capacity ◽  
Robot Manipulator ◽  
Time Interval ◽  
Planning Problem ◽  
Load Carrying Capacity ◽  
Objective Functions ◽  
Decision Variables ◽  
Load Carrying

A new methodology using a direct method for obtaining the best found trajectory planning and maximum dynamic load-carrying capacity (DLCC) is presented for a 5-degree of freedom (DOF) hybrid robot manipulator. A nonlinear constrained multiobjective optimization problem is formulated with four objective functions, namely, travel time, total energy involved in the motion, joint jerks, and joint acceleration. The vector of decision variables is defined by the sequence of the time-interval lengths associated with each two consecutive via-points on the desired trajectory of the 5-DOF robot generalized coordinates. Then this vector of decision variables is computed in order to minimize the cost function (which is the weighted sum of these four objective functions) subject to constraints on joint positions, velocities, acceleration, jerks, forces/torques, and payload mass. Two separate approaches are proposed to deal with the trajectory planning problem and the maximum DLCC calculation for the 5-DOF robot manipulator using an evolutionary optimization technique. The adopted evolutionary algorithm is the elitist nondominated sorting genetic algorithm (NSGA-II). A numerical application is performed for obtaining best found solutions of trajectory planning and maximum DLCC calculation for the 5-DOF hybrid robot manipulator.

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