Showing papers on "Vehicle dynamics published in 2011"
TL;DR: This paper provides a practical means to evaluate the ACC systems applying the sliding-mode controller and provides a reasonable proposal to design the ACC controller from the perspective of the practical string stability.
Abstract: In this paper, the practical string stability of both homogeneous and heterogeneous platoons of adaptive cruise control (ACC) vehicles, which apply the constant time headway spacing policy, is investigated by considering the parasitic time delays and lags of the actuators and sensors when building the vehicle longitudinal dynamics model. The proposed control law based on the sliding-mode controller can guarantee both homogeneous and heterogeneous string stability, if the control parameters and system parameters meet certain requirements. The analysis of the negative effect of the parasitic time delays and lags on the string stability indicates that the negative effect of the time delays is larger than that of the time lags. This paper provides a practical means to evaluate the ACC systems applying the sliding-mode controller and provides a reasonable proposal to design the ACC controller from the perspective of the practical string stability.
403 citations
TL;DR: In this paper, a nested PID steering control in vision-based autonomous vehicles is designed and experimentally tested to perform path following in the case of roads with an uncertain curvature.
304 citations
TL;DR: In this paper, the authors provide an overview of the latest advances in road vehicle suspension design, dynamics, and control, together with the authors' perspectives, in the context of vehicle ride, handling, and stability.
Abstract: This paper provides an overview of the latest advances in road vehicle suspension design, dynamics, and control, together with the authors' perspectives, in the context of vehicle ride, handling, and stability. The general aspects of road vehicle suspension dynamics and design are discussed, followed by descriptions of road-roughness excitations with a particular emphasis on road potholes. Passive suspension system designs and their effects on road vehicle dynamics and stability are presented in terms of in-plane and full-vehicle arrangements. Controlled suspensions are also reviewed and discussed. The paper concludes with some potential research topics, in particular those associated with the development of hybrid and electric vehicles.
302 citations
TL;DR: A nonlinear model predictive control method with a fast optimization algorithm is implemented to derive the vehicle control inputs based on road gradient conditions obtained from digital road maps and reveals the ability of the eco-driving system in significantly reducing fuel consumption of a vehicle.
Abstract: This paper presents a novel development of an ecological (eco) driving system for running a vehicle on roads with up-down slopes. Fuel consumed in a vehicle is greatly influenced by road gradients, aside from its velocity and acceleration characteristics. Therefore, optimum control inputs can only be computed through anticipated rigorous reasoning using information concerning road terrain, model of the vehicle dynamics, and fuel consumption characteristics. In this development, a nonlinear model predictive control method with a fast optimization algorithm is implemented to derive the vehicle control inputs based on road gradient conditions obtained from digital road maps. The fuel consumption model of a typical vehicle is formulated using engine efficiency characteristics and used in the objective function to ensure fuel economy driving. The proposed eco-driving system is simulated on a typical road with various shapes of up-down slopes. Simulation results reveal the ability of the eco-driving system in significantly reducing fuel consumption of a vehicle. The fuel saving behavior is graphically illustrated, compared, and analyzed to focus on the significance of this development.
298 citations
01 Jun 2011
TL;DR: This paper investigates the cooperative tracking control problem for a group of Lagrangian vehicle systems with directed communication graph topology and proposes a design method for a distributed adaptive protocol which guarantees that all the networked systems synchronize to the motion of a target system.
Abstract: This paper investigates the cooperative tracking control problem for a group of Lagrangian vehicle systems with directed communication graph topology. All the vehicles can have different dynamics. A design method for a distributed adaptive protocol is given which guarantees that all the networked systems synchronize to the motion of a target system. The dynamics of the networked systems, as well as the target system, are all assumed unknown. A neural network (NN) is used at each node to approximate the distributed dynamics. The resulting protocol consists of a simple decentralized proportional-plus-derivative term and a nonlinear term with distributed adaptive tuning laws at each node. The case with nonconstant NN approximation error is considered. There, a robust term is added to suppress the external disturbances and the approximation errors of the NNs. Simulation examples are included to demonstrate the effectiveness of the proposed algorithms.
253 citations
TL;DR: A new approach to analyzing the economic impacts of vehicle-to-grid (V2G) regulation reserves is established by simulating the restrictions arising from unpredictable mobility requests by vehicle users and it is shown that negative secondary control is economically the most beneficial for electric vehicles.
Abstract: This study establishes a new approach to analyzing the economic impacts of vehicle-to-grid (V2G) regulation reserves by simulating the restrictions arising from unpredictable mobility requests by vehicle users. A case study for Germany using average daily values (in the following also called the “static” approach) and a dynamic simulation including different mobility use patterns are presented. Comparing the dynamic approach with the static approach reveals a significant difference in the power a vehicle can offer for ancillary services and provides insights into the necessary size of vehicle pools and possible adaptations required in the regulation market to render V2G feasible. In the static approach it is shown that negative secondary control is economically the most beneficial for electric vehicles because it offers the highest potential for charging with “low-priced” energy from negative regulation reserves. A Monte Carlo simulation using stochastic mobility behavior results in a 40% reduction of the power available for regulation compared to the static approach. Because of the high value of power in the regulation market, this finding has a strong impact on the resulting revenues. Further, we demonstrate that, for the data used, a pool size of 10 000 vehicles seems reasonable to balance the variation in each individual's driving behavior. In the case of the German regulation market, which uses monthly bids, a daily or hourly bid period is recommended. This adaptation would be necessary to provide individual regulation assuming that the vehicles are primarily used for mobility reasons and cannot deliver the same amount of power every hour of the week.
246 citations
TL;DR: In this paper, a dynamic modeling and observation method is proposed to estimate the lateral tire forces at each wheel in order to prevent road side accidents, and two observers derived from extended and unscented Kalman filtering techniques are compared.
Abstract: The principal concerns in driving safety with standard vehicles or cybercars are understanding and preventing risky situations. A close examination of accident data reveals that losing control of the vehicle is the main reason for most car accidents. To help to prevent such accidents, vehicle-control systems may be used, which require certain input data concerning vehicle-dynamic parameters and vehicle-road interaction. Unfortunately, some fundamental parameters, like tire-road forces and sideslip angle are difficult to measure in a car, for both technical and economic reasons. Therefore, this study presents a dynamic modeling and observation method to estimate these variables. One of the major contributions of this study, with respect to our previous work and to the largest literature in the field of the lateral dynamic estimation, is the fact that lateral tire force at each wheel is discussed in details. To address system nonlinearities and unmodeled dynamics, two observers derived from extended and unscented Kalman filtering techniques are proposed and compared. The estimation process method is based on the dynamic response of a vehicle instrumented with available and potentially integrable sensors. Performances are tested using an experimental car. Experimental results demonstrate the ability of this approach to provide accurate estimations, and show its practical potential as a low-cost solution for calculating lateral tire forces and sideslip angle.
228 citations
TL;DR: In this article, a review of existing models for railway vehicle suspension components and their use in railway vehicle dynamics multi-body simulations is presented, and the required level of detail of component models in view of the accuracy expected from the overall simulation model is discussed.
Abstract: Suspension components play key roles in the running behaviour of rail vehicles, and therefore, mathematical models of suspension components are essential ingredients of railway vehicle multi-body models. The aims of this paper are to review existing models for railway vehicle suspension components and their use for railway vehicle dynamics multi-body simulations, to describe how model parameters can be defined and to discuss the required level of detail of component models in view of the accuracy expected from the overall simulation model. This paper also addresses track models in use for railway vehicle dynamics simulations, recognising their relevance as an indispensable component of the system simulation model. Finally, this paper reviews methods presently in use for the checking and validation of the simulation model.
196 citations
TL;DR: In this article, an unscented Kalman filter is used for estimation purposes, since it is based on a numerically efficient nonlinear stochastic estimation technique, and an advanced vertical tyre load calculation method is developed that additionally considers the vertical tyre stiffness and increases the estimation accuracy.
Abstract: Vehicle dynamics control (VDC) systems require information about system variables, which cannot be directly measured, e.g. the wheel slip or the vehicle side-slip angle. This paper presents a new concept for the vehicle state estimation under the assumption that the vehicle is equipped with the standard VDC sensors. It is proposed to utilise an unscented Kalman filter for estimation purposes, since it is based on a numerically efficient nonlinear stochastic estimation technique. A planar two-track model is combined with the empiric Magic Formula in order to describe the vehicle and tyre behaviour. Moreover, an advanced vertical tyre load calculation method is developed that additionally considers the vertical tyre stiffness and increases the estimation accuracy. Experimental tests show good accuracy and robustness of the designed vehicle state estimation concept.
193 citations
TL;DR: In this paper, the translational degrees of freedom of the quadrotor are decoupled, and time-optimal trajectories are found for each degree of freedom separately.
193 citations
09 May 2011
TL;DR: This work extends the classic control problem of the inverted pendulum by placing the pendulum on top of a quadrotor aerial vehicle, using a ‘Virtual Body Frame’ for the time-invariant description of curved trajectories.
Abstract: We extend the classic control problem of the inverted pendulum by placing the pendulum on top of a quadrotor aerial vehicle. Both static and dynamic equilibria of the system are investigated to find nominal states of the system at standstill and on circular trajectories. Control laws are designed around these nominal trajectories. A yaw-independent description of quadrotor dynamics is introduced, using a ‘Virtual Body Frame’. This allows for the time-invariant description of curved trajectories. The balancing performance of the controller is demonstrated in the ETH Zurich Flying Machine Arena testbed. Development potential for the future is highlighted, with a focus on applying learning methodology to increase performance by eliminating systematic errors that were seen in experiments.
TL;DR: The results from simulations and a hardware experiment demonstrate that the proposed algorithm can improve the fleet objective by temporarily having one vehicle sacrifice its individual objective, showing the cooperative behavior.
Abstract: Motivated by recent research on cooperative unmanned aerial vehicles (UAVs), this paper introduces a new cooperative distributed trajectory optimization approach for systems with independent dynamics but coupled objectives and hard constraints. The overall goal is to develop a distributed approach that solves small subproblems while minimizing a fleet-level objective. In the new algorithm, vehicles solve their subproblems in sequence while generating feasible modifications to the prediction of other vehicles' plans. In order to avoid reproducing the global optimization, the decisions of other vehicles are parameterized using a much smaller number of variables than in the centralized formulation. This reduced number of variables is sufficient to improve the cooperation between vehicles without significantly increasing the computational effort involved. The resulting algorithm is shown to be robustly feasible under the action of unknown but bounded disturbances. Furthermore, the fleet objective function is proven to monotonically decrease as the algorithm cycles through the vehicles in the fleet and over the time. The results from simulations and a hardware experiment demonstrate that the proposed algorithm can improve the fleet objective by temporarily having one vehicle sacrifice its individual objective, showing the cooperative behavior.
Book•
21 Sep 2011
TL;DR: In this article, the authors define multibody dynamics tailored to ground vehicles, including steering, suspension, and wheel and tire components, and apply them to a quarter car model and a three-dimensional vehicle.
Abstract: Introduction Units and Quantities Terminology Definitions Multibody Dynamics tailored to Ground Vehicles A Quarter Car Model Exercises Road Modeling Aspects Deterministic Profiles Random Profiles Exercises Tire Introduction Contact Geometry Steady State Forces and Torques Combined Forces Bore Torque Different Influences on Tire Forces and Torques First Order Tire Dynamics Exercises Drive Train Components and Concepts Wheel and Tire Differentials Transmission Clutch Power Sources Exercises Suspension System Purpose and Components Some Examples Steering Systems Kinematics of a Double Wishbone Suspension Exercises Force Elements Standard Force Elements Dynamic Force Elements Exercises Vertical Dynamics Goals From Complex to Simple Models Basic Tuning Optimal Damping Practical Aspects Nonlinear Suspension Forces Sky Hook Damper Exercises Longitudinal Dynamics Dynamic Wheel Loads Maximum Acceleration Driving and Braking Drive and Brake Pitch Exercises Lateral Dynamics Kinematic Approach Steady State Cornering Simple Handling Model Mechatronic Systems Exercises Driving Behavior of Single Vehicles Three-Dimensional Vehicle Model Driver Model Standard Driving Maneuvers Coach with Different Loading Conditions Different Rear Axle Concepts for a Passenger Car Exercises Bibliography Index
TL;DR: The analytical model that is developed is important to study the flight dynamics and passive stability of flying animals, as well as to develop flapping-wing micro air vehicles (MAVs) with stable and maneuverable flight, which is achieved through passive dynamic stability and active flight control.
Abstract: Body movements of flying insects change their effective wing kinematics and, therefore, influence aerodynamic force and torque production. It was found that substantial aerodynamic damping is produced by flapping wings through a passive mechanism termed “flapping countertorque” during fast yaw turns. We expand this study to include the aerodynamic damping that is produced by flapping wings during body translations and rotations with respect to all its six principal axes-roll, pitch, yaw, forward/backward, sideways, and heave. Analytical models were derived by the use of a quasi-steady aerodynamic model and blade-element analysis by the incorporation of the effective changes of wing kinematics that are caused by body motion. We found that aerodynamic damping, in all these cases, is linearly dependent on the body translational and angular velocities and increases with wing-stroke amplitude and frequency. Based on these analytical models, we calculated the stability derivatives that are associated with the linearized flight dynamics at hover and derived a complete 6-degree-of-freedom (6-DOF) dynamic model. The model was then used to estimate the flight dynamics and stability of four different species of flying insects as case studies. The analytical model that is developed in this paper is important to study the flight dynamics and passive stability of flying animals, as well as to develop flapping-wing micro air vehicles (MAVs) with stable and maneuverable flight, which is achieved through passive dynamic stability and active flight control.
TL;DR: Simulation results based on a high-fidelity CarSim full-vehicle model show that the system can reliably estimate the tire-road friction coefficient independent of vehicle longitudinal motion.
Abstract: This paper presents a novel real-time tire-road friction coefficient estimation method that is independent of vehicle longitudinal motion for ground vehicles with separable control of the front and rear wheels. The tire-road friction coefficient information is of critical importance for vehicle dynamic control systems and intelligent autonomous vehicle applications. In this paper, the vehicle longitudinal-motion-independent tire-road friction coefficient estimation method consists of three main components: 1) an observer to estimate the internal state of a dynamic LuGre tire model; 2) an adaptive control law with a parameter projection mechanism to track the desired vehicle longitudinal motion in the presence of tire-road friction coefficient uncertainties and actively injected braking excitation signals; and 3) a recursive least square estimator that is independent of the control law, to estimate the tire-road friction coefficient in real time. Simulation results based on a high-fidelity CarSim full-vehicle model show that the system can reliably estimate the tire-road friction coefficient independent of vehicle longitudinal motion.
TL;DR: It has been shown from simulation studies that vehicle maneuverability, lateral stability, and rollover mitigation performance can be significantly improved by the proposed driving controller.
Abstract: This paper describes a driving control algorithm for four-wheel-drive (4WD) electric vehicles equipped with two motors at front and rear driving shafts to improve vehicle maneuverability, lateral stability, and rollover prevention. The driving control algorithm consists of the following three parts: 1) a supervisory controller that determines the control mode, the admissible control region, and the desired dynamics, such as the desired speed and yaw rate; 2) an upper level controller that computes the traction force input and the yaw moment input to track the desired dynamics; and 3) a lower level controller that determines actual actuator commands, such as the front/rear driving motor torques and independent brake torques. The supervisory controller computes the admissible control region, namely, the relationship between the vehicle speed and the maximum curvature of the vehicle considering the maximum steering angle, lateral stability, and rollover prevention. In the lower level controller, a wheel slip controller is designed to keep the slip ratio at each wheel below a limit value. In addition, an optimization-based control allocation strategy is used to map the upper level and wheel slip control inputs to actual actuator commands, taking into account the actuator constraints. Numerical simulation studies have been conducted to evaluate the proposed driving control algorithm. It has been shown from simulation studies that vehicle maneuverability, lateral stability, and rollover mitigation performance can be significantly improved by the proposed driving controller.
TL;DR: A multiple point mass with a single-coordinate dynamic model that reflects resistive and transient impacts is derived, and based on this, computationally inexpensive robust adaptive control designs with optimal task distribution for speed and position tracking are proposed under traction/braking nonlinearities and saturation limitations.
Abstract: The problem of the position and velocity tracking control of high-speed trains becomes interesting yet challenging when simultaneously considering inevitable factors such as the resistive friction and aerodynamic drag forces, the interactive impacts among the vehicles, and the nonlinear traction/braking notches inherent in train systems. In this paper, a multiple point mass with a single-coordinate dynamic model that reflects resistive and transient impacts is derived, and based on this, computationally inexpensive robust adaptive control designs with optimal task distribution for speed and position tracking are proposed under traction/braking nonlinearities and saturation limitations. It is shown that the proposed method is not only robust to external disturbances, aerodynamic resistance, mechanical resistance, and transient impacts but adaptive to unknown system parameters as well. The effectiveness of the proposed approach is also confirmed through numerical simulations.
TL;DR: Adapt and distributed algorithms for motion coordination of a group of m vehicles must service demands whose time of arrival, spatial location, and service requirement are stochastic to minimize the average time demands spend in the system.
Abstract: In this paper, we present adaptive and distributed algorithms for motion coordination of a group of m vehicles. The vehicles must service demands whose time of arrival, spatial location, and service requirement are stochastic; the objective is to minimize the average time demands spend in the system. The general problem is known as the m-vehicle Dynamic Traveling Repairman Problem (m-DTRP). The best previously known control algorithms rely on centralized task assignment and are not robust against changes in the environment. In this paper, we first devise new control policies for the 1-DTRP that: i) are provably optimal both in light-load conditions (i.e., when the arrival rate for the demands is small) and in heavy-load conditions (i.e., when the arrival rate for the demands is large), and ii) are adaptive, in particular, they are robust against changes in load conditions. Then, we show that specific partitioning policies, whereby the environment is partitioned among the vehicles and each vehicle follows a certain set of rules within its own region, are optimal in heavy-load conditions. Building upon the previous results, we finally design control policies for the m-DTRP that i) are adaptive and distributed, and ii) have strong performance guarantees in heavy-load conditions and stabilize the system in any load condition.
TL;DR: A robust and simple algorithm for an attitude and heading reference system (AHRS) based on low-cost MEMS inertial and magnetic sensors based on a gain-scheduled complementary filter augmented by an acceleration-based switching architecture to yield robust performance, even when the vehicle is subject to strong accelerations.
Abstract: This paper describes a robust and simple algorithm for an attitude and heading reference system (AHRS) based on low-cost MEMS inertial and magnetic sensors. The proposed approach relies on a gain-scheduled complementary filter, augmented by an acceleration-based switching architecture to yield robust performance, even when the vehicle is subject to strong accelerations. Experimental results are provided for a road captive test during which the vehicle dynamics are in high-acceleration mode and the performance of the proposed filter is evaluated against the output from a conventional linear complementary filter.
TL;DR: A nonlinear observer is presented for estimating the longitudinal and lateral velocities based on Dugoff's tire model and vehicle dynamics and the robustness of the observer with respect to additive disturbances is analyzed with the help of input-to-state stability theory.
Abstract: This brief presents a nonlinear observer for estimating the longitudinal and lateral velocities based on Dugoff's tire model and vehicle dynamics. The observer has a fixed gain structure and can make full use of information about acceleration measurements and nonlinear vehicle model. A sufficient condition is derived to guarantee the stability of the observer, and the robustness of the observer with respect to additive disturbances is analyzed with the help of input-to-state stability theory. The performance of the observer is compared with that of existing approaches and evaluated experimentally under a variety of maneuvers and road conditions.
TL;DR: In this paper, the transmission kinematics and dynamics of a DCT were investigated, considering all the possible configurations that can take place in relation to the various power flow paths, and the resulting sets of equations are written in an indexed form that can be easily integrated in a vehicle model, thus allowing the description of both gear shift transients and operation with a specific gear.
TL;DR: In this article, a control scheme to stabilize rear-wheel-drive (RWD) vehicles with respect to high-sideslip cornering (drifting) steady states using coordinated steering and drive torque control inputs is presented.
TL;DR: This method is able to provide cycle-by-cycle queue length estimation for signalized intersections with sampled vehicle trajectories as the only input, and the results indicate that this trajectory-based approach is promising.
Abstract: Queue length estimation is an important component of intersection performance measurement. Different approaches based on different data sources have been presented. With the latest developments in vehicle detection technologies, especially probe vehicle technologies, use of vehicle trajectory data has become possible. In this paper, an improved method for queue length estimation for signalized intersections is proposed. This method is able to provide cycle-by-cycle queue length estimation for signalized intersections with sampled vehicle trajectories as the only input. The keystone of the entire approach is the concept of the critical point (CP), which represents the changing vehicle dynamics. A CP extraction algorithm is introduced to identify CPs from raw trajectories. Using the CPs related to queue formation and dissipation, the authors propose an improved queue length estimation method based on shock waves. The performance of this approach is evaluated with several data sets under different flow and s...
TL;DR: This paper demonstrates that simple lookahead control schemes for lanekeeping are provably robust even at the limits of tire adhesion, and can be coupled with longitudinal control based on path position and wheel slip to create an autonomous racecar.
TL;DR: In this article, a nonlinear controller using backstepping technique is designed for the clutch-slip control, and the controller is designed such that the error dynamics is input-to-state stable.
Abstract: To improve the shift quality of vehicles with clutch-to-clutch gearshifts, a nonlinear controller using backstepping technique is designed for the clutch-slip control. Model uncertainties including steady-state errors and unmodeled dynamics are also considered as additive disturbance inputs, and the controller is designed such that the error dynamics is input-to-state stable. Lookup tables, which are widely used to represent complex nonlinear characteristics of engine systems, appear in their original form in the designed nonlinear controller. Finally, the designed controller is tested on an AMESim power train simulation model. Comparisons with an existing linear algorithm are given as well.
18 Aug 2011
TL;DR: In this article, a real-time estimation method based on Kalman filter is proposed for calculating loads on the wheels using road profile, which is based on the dynamic response of a vehicle instrumented with available sensors.
Abstract: Knowledge of vehicle dynamic data is essential for the enhancement of active safety systems such as suspensions and trajectory control systems. Vehicle controllability analysis on real roads can be obtained only if valid road profile and tire road friction model are known. With regard to the road profile, this study focuses on a real-time estimation method based on Kalman filter. Besides, this paper presents a method for calculating loads on the wheels using road profile. The proposed method is based on the dynamic response of a vehicle instrumented with available sensors. The estimation process is applied and compared to real experimental data obtained with two inertial methods in real conditions. Experimental results show the accuracy and the potential of the proposed estimation process.
TL;DR: This technical note treats the challenging control problem of tracking a desired continuous trajectory for a maneuverable autonomous vehicle in the presence of gravity, buoyancy and fluid dynamic forces and moments by focusing on an autonomous underwater vehicle application.
Abstract: This technical note treats the challenging control problem of tracking a desired continuous trajectory for a maneuverable autonomous vehicle in the presence of gravity, buoyancy and fluid dynamic forces and moments. A realistic dynamics model that applies to maneuverable vehicles moving in 3-D Euclidean space is used for obtaining this control scheme. While applications of this control scheme include autonomous aerial and underwater vehicles, we focus on an autonomous underwater vehicle (AUV) application because of its richer, more nonlinearly coupled, dynamics. The desired trajectory and trajectory tracking errors are globally characterized in the nonlinear state space. Almost global asymptotic stability to the desired trajectory in the nonlinear state space is demonstrated both analytically and through numerical simulations.
TL;DR: A new nonlinear controller to adjust the height of the vehicle sprung mass (height control) and to regulate the roll and pitch angles of the Vehicle body (leveling control) by an air suspension system is proposed.
Abstract: Electronically controlled air suspension systems have been used in vehicles to improve ride comfort and handling safety by adjusting vehicle height. This paper proposes a new nonlinear controller to adjust the height of the vehicle sprung mass (height control) and to regulate the roll and pitch angles of the vehicle body (leveling control) by an air suspension system. A sliding mode control algorithm is designed to improve the tracking accuracy of the control and to overcome nonlinearities and uncertainties in the air suspension system. A mathematical model of the air suspension system is formulated in a nonlinear affine form to describe the dynamic behavior of the system and to derive the control algorithm. The sliding mode observer is also designed to estimate the pressures inside four air springs. The effectiveness and performance of the proposed control algorithm are verified by simulations and actual vehicle tests.
TL;DR: Experimental data confirm that the developed algorithms perform reliably in a number of different maneuvers that include constant steering, ramp steering, double lane change, and sine with dwell steering tests.
Abstract: In active rollover prevention systems, a real-time rollover index, which indicates the likelihood of the vehicle to roll over, is used. This paper focuses on state and parameter estimation for reliable computation of the rollover index. Two key variables that are difficult to measure and play a critical role in the rollover index are found to be the roll angle and the height of the center of gravity of the vehicle. Algorithms are developed for real-time estimation of these variables. The algorithms investigated include a sensor fusion algorithm and a nonlinear dynamic observer. The sensor fusion algorithm requires a low-frequency tilt-angle sensor, whereas the dynamic observer utilizes only a lateral accelerometer and a gyroscope. The stability of the nonlinear observer is shown using Lyapunov's indirect method. The performance of the developed algorithms is investigated using simulations and experimental tests. Experimental data confirm that the developed algorithms perform reliably in a number of different maneuvers that include constant steering, ramp steering, double lane change, and sine with dwell steering tests.
01 Jun 2011
TL;DR: In this article, a search algorithm based on A* for multi-objective 4-D vehicle motion planning (three spatial and one time dimensions) is presented, which is principally motivated by the need for offline and online motion planning for autonomous UAVs.
Abstract: This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4-D vehicle motion planning (three spatial and one time dimensions). The research is principally motivated by the need for offline and online motion planning for autonomous unmanned aerial vehicles (UAVs). For UAVs operating in large dynamic uncertain 4-D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and a grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles, and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle, and velocity trajectory segments. These segments are approximated with a grid-based cell sequence that provides an inherent tolerance to uncertainty. The computational efficiency is achieved by using variable successor operators to create a multiresolution memory-efficient lattice sampling structure. The simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of a vector neighborhood-based A*.