A guidance‐based motion‐planning methodology for the docking of autonomous vehicles

In this paper, a generic line‐of‐sight‐sensing (LOS)‐based guidance methodology is proposed for the docking of autonomous vehicles/robotic end‐effectors: A multi‐LOS task‐space sensing system is used in conjunction with a guidance algorithm in a closed‐loop feedback environment. The novelty of the overall system is its applicability to cases that do not allow for the direct proximity measurement of the vehicle's pose (position and orientation). In such instances, a guidance‐based technique must be employed to move the vehicle to its desired pose using corrective actions at the final stages of its motion. Namely, after the vehicle/end‐effector has failed to move to its desired docking pose within acceptable tolerances, LOS sensors initiate short‐range corrective motion commands. The objective of the proposed guidance method is, thus, to successfully minimize the systematic errors of the vehicle, accumulated after a long‐range motion, while allowing it to converge within the random noise limits. An additional advantage of the proposed system is its applicability to varying vehicle mobility requirements for high‐precision docking. The proposed system was successfully tested via simulation on a 6 degree‐of‐freedom (DOF) vehicle. Numerous simulation tests of the behavior of the vehicle under the command of the guidance algorithm were conducted, one of which is presented herein. © 2005 Wiley Periodicals, Inc.     

Short-range guidance of autonomous vehicles—a comparative study

In this paper, two generic line-of-sight (LOS) sensing-based short-range guidance methodologies are presented for the docking of autonomous vehicles. The first method utilizes a passive LOS sensing scheme to provide vehicle corrective motions, while the latter method utilizes active sensing. The novelty of the proposed guidance methodologies is their applicability to situations that do not allow for direct proximity measurements of the vehicle. In such instances, one must employ a guidance-based technique to move the vehicle to its desired pose using corrective actions at the final stages of its motion. The objective of both proposed guidance methods is, thus, to successfully minimize the systematic errors of the vehicle, while allowing it to converge to its desired pose within random noise limits. Both techniques were successfully tested via simulations and are discussed herein in terms of convergence rate and accuracy, in addition to the types of localization problems that each method should be used in.     

A two‐step control approach for docking of autonomous underwater vehicles

This paper presents a novel integrated guidance and control strategy for docking of autonomous underwater vehicles. The approach to the base, and hence the control design, is divided in two steps: (i) in the first, at higher speed, the vehicle dynamics is assumed to be underactuated, and an appropriate control law is derived to steer the vehicle towards the final docking path, achieving convergence to zero of the appropriate error variables for almost all initial conditions; (ii) in the second stage, at low speed, the vehicle is assumed to be fully actuated, and a robust control law is designed that achieves convergence to zero of the appropriate error variables for all initial conditions, in the presence of parametric model uncertainty. Simulations are presented illustrating the performance of the proposed controllers, including model uncertainty and sensor noise. Copyright © 2014 John Wiley & Sons, Ltd.     

Research on disturbance rejection motion control method of USV for UUV recovery

The recovery of unmanned underwater vehicle (UUV) by unmanned surface vehicle (USV) has the characteristics of autonomy, safety, and efficiency. Taking the recovery of UUV by USV as the engineering background, this paper studies the guidance and anti-interference motion control of USV in the recovery process. Aiming at the problem of dynamic guidance when recovering UUV, the USV guidance strategy for UUV recovery is studied. Fuzzy guidance is introduced as the dynamic terminal guidance method, and a layered guidance strategy combining classical guidance and fuzzy guidance is proposed. On the basis of the theory of compact form dynamic linearization-based model-free adaptive control (CFDL-MFAC), the motion control of USV in the process of recovering UUV under the influence of model perturbation, external interference, and other uncertainties is studied. Theoretical analysis and experimental results show that there is a contradiction in the matching of dynamic change speed between the USV heading control subsystem and CFDL-MFAC. By introducing the difference item into the standard control criterion to weaken the integral effect in the heading control subsystem of USV, a difference-type compact format model-free adaptive control method (DCFDL-MFAC) is proposed, and the stability of DCFDL-MFAC method is proved theoretically. The effectiveness and practicability of the proposed method are verified by simulation tests and field tests of “Dolphin IB” small USV.     

Flatness-based hypersonic reentry guidance of a lifting-body vehicle

This paper deals with the design of a guidance algorithm for the hypersonic phase of a lifting-body vehicle. The guidance strategy is based on a particular kind of nonlinear dynamic inversion, the so-called flatness approach. The main advantage of this approach is that the longitudinal guidance law is in-flight self-adaptive to any feasible hypersonic trajectory and can be written in analytical form with a small set of design parameters. Therefore, the required on-board computational resources are limited, and a reduced off-line design effort is needed for the change of vehicle parameters. Moreover, the closed-loop longitudinal guidance commands are computed on-board in a coupled way without relying on an explicit deceleration profile. Consequently, the approach leads to an efficient management of the degree of freedom associated with the angle-of-attack. PID controllers are then designed based on the longitudinal flat model in order to circumvent uncertainties and parameters dispersions. The crossrange is controlled by a series of bank reversals determined by an azimuth error deadband. The robustness and performance of the proposed guidance law are assessed by performing Monte Carlo runs with various sets of dispersions.     

Adaptive disturbance observer‐based finite‐time continuous fault‐tolerant control for reentry RLV

The control effectors of reusable launch vehicle (RLV) can produce significant perturbations and faults in reentry phase. Such a challenge imposes tight requirements to enhance the robustness of vehicle autopilot. Focusing on this problem, a novel finite‐time fault‐tolerant control strategy is proposed for reentry RLV in this paper. The key of this strategy is to design an adaptive‐gain multivariable finite‐time disturbance observer (FDO) to estimate the synthetical perturbation with unknown bounds, which is composed of model uncertainty, external disturbance, and actuator fault considered as the partial loss of actuator effectiveness in this work. Then, combined with the finite‐time high‐order observer and differentiator, a continuous homogeneous second‐order sliding mode controller based on the terminal sliding mode and super‐twisting algorithm is designed to achieve a fast and accurate RLV attitude tracking with chattering attenuation. The main features of the integrated control strategy are that the adaptation algorithm of FDO can achieve non‐overestimating values of the observer gains and the second‐order super‐twisting sliding mode approach can obtain a more elegant solution in finite time. Finally, simulation results of classical RLV (X‐33) are provided to verify the effectiveness and robustness of the proposed fault‐tolerant controller in tracking the guidance commands. Copyright © 2017 John Wiley & Sons, Ltd.     

Coordinated Control Architecture for Motion Management in ADAS Systems

Advanced driver assistance systems (ADAS) seek to provide drivers and passengers of automotive vehicles increased safety and comfort. Original equipment manufacturers are integrating and developing systems for distance keeping, lane keeping and changing and other functionalities. The modern automobile is a complex system of systems. How the functionalities of advanced driver assistance are implemented and coordinated across the systems of the vehicle is generally not made available to the wider research community by the developers and manufactures. This paper seeks to begin filling this gap by assembling open source physics models of the vehicle dynamics and ADAS command models. Additionally, in order to facilitate ADAS development and testing without having access to the details of ADAS, a coordinated control architecture for motion management is also proposed for distributing ADAS motion control commands over vehicle systems. The architecture is demonstrated in a case study where motion is coordinated between the steering and the braking systems, which are typically used only for a single functionality. The integrated vehicle and system dynamics using the coordinated control architecture are simulated for various driving tasks. It is seen that improved trajectory following can be achieved by the proposed coordinated control architecture. The models, simulations and control architecture are made available for open access.      

Lining-Up Control Strategies for N-trailer Vehicles

Maneuvers performed with tractor-trailers vehicles (N-trailers) belong to the most demanding motion control tasks in the transportation practice. Very frequent maneuvers concern the lining-up process of a vehicle chain, usually as a preliminary stage which prepares the system to subsequent parking/docking maneuvers. The most common lining-up control approach results from utilization of the open-loop asymptotic stability of N-trailer joint-angle dynamics in the forward motion. However, in case of long trailers this approach appears very inefficient especially if the available motion space is substantially limited. By using the triangular forms of joint-angle dynamics the problem of lining-up control for N-trailers is analyzed in the paper by considering two alternative strategies: active lining-up (feedback control) and passive lining-up (open-loop control). The two strategies are compared in the context of their practical effectiveness, and how the effectiveness depends on kinematic parameters of the trailers and their interconnections. It is revealed why the active strategy can be much more efficient in most practical cases. Theoretical considerations are validated by results of numerical simulations and experiments conducted with a laboratory-scale three-trailer robotic vehicle.     

Energy-based guidance of an underactuated unmanned underwater vehicle on a helical trajectory

This paper presents a motion control system for guidance of an underactuated Unmanned Underwater Vehicle (UUV) on a helical trajectory. The control strategy is developed using Port-Hamiltonian theory and interconnection and damping assignment passivity-based control. Using energy routing, the trajectory of a virtual fully actuated plant is guided onto a vector field. A tracking controller is then used that commands the underactuated plant to follow the velocity of the virtual plant. An integral control is inserted between the two control layers, which adds robustness and disturbance rejection to the design.     

Autonomous mobile robot model predictive control

This paper presents model predictive control of an autonomous vehicle. Simulation and experimental results have been shown and compared with input–output linearization method. The results obtained show that the MPC is an efficient method that allows for accurate control and navigation of an autonomous vehicle. Model based predictive control is tested in simulations for motion on an inclined plane. This is done to prepare future work regarding the avoidance of the violation of the smoothness condition for exact linearization, while at the same time by modifying the input commands the geometric path planning results are conserved. The approach is presented for the wheel-ground slippage and tip-over avoidance of the three-wheeled vehicle for inclined plane motion. A complete three-dimensional dynamic model using Newtonian dynamics is also presented. Simulation results using a three-wheeled vehicle built in our laboratory illustrate the performance of the proposed controller.     

Active sonar-based bottom-following for unmanned underwater vehicles

The problem of high-precision bottom-following in the proximity of the seabed for open-frame unmanned underwater vehicles (UUVs) is addressed in this paper. The suggested approach consists of the integration of a guidance and control system with an active multi-hypothesis extended Kalman filter, able to estimate the motion of the vehicle with respect to the bottom profile. The guidance module is based on the definition of a suitable Lyapunov function associated with the bottom-following task, while the motion controller is a conventional autopilot, performing autoheading, autodepth, and autospeed. The motion of the vehicle is estimated from range and bearing measurements supplied by a high-frequency pencil-beam profiling sonar. Moreover, a general-purpose sensor-based guidance and control system for advanced UUVs, able to manage active sensing-based guidance and motion estimation modules, is presented. An application of the proposed architecture to execute high-precision bottom-following using Romeo, a prototype UUV, developed by the Robotics Dept. of the Istituto Automazione Navale, is described. Experimental results of tests, conducted in a high-diving pool with the vehicle equipped with a sonar profiler, are presented.     

基于准最大最小模型预测控制的AUV视觉对接

针对六自由度自主式水下机器人(autonomous underwater vehicle, AUV)视觉对接这一重要课题,提出一种基于融合深度信息的改进准最大最小模型预测控制(quasi-min-max model predictive control, QMM-MPC)方法,有效提高复杂水下视觉伺服对接系统性能.首先,针对水下AUV视觉由于能见度低导致深度信息存在不确定性的影响,建立新的六自由度AUV视觉伺服模型;然后,结合AUV运动和图像特征运动的测量数据,设计在线深度估计器,同时提出结合多李雅普诺夫函数的QMM-MPC算法,通过求取凸多面体中各顶点不同上界值,降低传统QMM-MPC算法中单李雅普诺夫函数上界所带来的强保守性;最后,通过仿真验证所提出方法的有效性和优越性.     

Method for tracking of environmental level sets by a unicycle-like vehicle

We consider a single Dubins-like vehicle traveling with a constant longitudinal speed in a planar region supporting an unknown field distribution. A sensor provides the distribution value at the vehicle location. We present a new sliding mode control method for tracking environmental level sets: the vehicle is steered to the set where the distribution assumes a pre-specified value and circulates along this set afterwards. The proposed control algorithm does not employ gradient estimation and is non-demanding with respect to both computation and motion. Its mathematically rigorous justification is provided. The effectiveness of the proposed guidance law is confirmed by computer simulations.     

Feature correspondence and motion recovery in vehicle planar navigation

This paper describes a strategy to feature point correspondence and motion recovery in vehicle navigation. A transformation of the image plane is proposed that keeps the motion of the vehicle on a plane parallel to the transformed image plane. This permits to define linear tracking filters to estimate the real-world positions of the features, and allows us to select the matches that accomplish the rigidity of the scene by a Hough transform. Candidate correspondences are selected by similarity, taking into account the smoothness of motion. Further processing brings out the final matching. The methods have been tested in a real application.     

A highly scalable path-following controller for N-trailers with off-axle hitching

The paper presents a highly scalable nonlinear cascaded-like path-following feedback controller for N-trailer robotic vehicles equipped with arbitrary number of off-axle hitched trailers. In contrast to the other path-following control laws proposed in the literature for N-trailer robots, the presented control approach does not require determination of the shortest distance to a reference path. By introducing the so-called segment-platooning reference paths, and under the sign-homogeneity assumption for hitching offsets, the asymptotic following is guaranteed for both constant- and varying-curvature reference paths using either backward or forward vehicle motion strategy with a guidance point fixed on the last trailer. The paper contains experimental results obtained with a 3-trailer laboratory-scale vehicle.     

Three-dimensional optimal path planning for waypoint guidance of an autonomous underwater vehicle

In this paper, optimal three-dimensional paths are generated offline for waypoint guidance of a miniature Autonomous Underwater Vehicle (AUV). Having the starting point, the destination point, and the position and dimension of the obstacles, the AUV is intended to systematically plan an optimal path toward the target. The path is defined as a set of waypoints to be passed by the vehicle. Four criteria are considered for evaluation of an optimal path; they are “total length of path”, “margin of safety”, “smoothness of the planar motion” and “gradient of diving”. A set of Pareto-optimal solutions is found where each solution represents an optimal feasible path that cannot be outrun by any other path considering all four criteria. Then, a proposed three-dimensional guidance system is used for guidance of the AUV through selected optimal paths. This system is inspired from the Line-of-Sight (LOS) guidance strategy; the idea is to select the desired depth, presumed proportional to the horizontal distance of the AUV and the target. To develop this guidance strategy, the dynamic modeling of this novel miniature AUV is also derived. The simulation results show that this guidance system efficiently guides the AUV through the optimal paths.     

航天器交会对接的模型预测与反演制导控制

面向空间交会对接和停靠的任务需求,将航天器相对制导控制系统视为离散时间控制系统.利用系统状态转移模型外推预测相对运动状态偏差,在每个控制周期中推力恒定的假设下,根据轨控作用对系统状态的影响规律,采用广义逆方法反演得到交会对接制导控制序列.对时间约束下的基于空间相对运动状态转移预测与反演的相对制导控制律进行设计,讨论该方法在实际应用中的一些特点.预测与反演制导控制中的控制输出直接表示为轨控加速度,更符合工程实际情况.近圆轨道的交会对接仿真结果表明,所提出的方法能够实现精度更高、更为柔顺平滑的交会对接,在轨控速度增量和推力器输出上也具有更好的工程适用性.     

Asynchronous control of rotation and translation for a robot vehicle

Robot arms require an ‘arm controller’ to command joint motors to achieve a coordinated motion in an external Cartesian coordinate space. In the same sense, robot vehicles require a ‘vehicle controller’ to command the motors to achieve a coordinated motion specified in terms of an external Cartesian coordinate space. This paper presents the design of a general purpose vehicle controller.

The vehicle controller is designed as a three-layer structure. The top layer is an interpreter which assures a control protocol based on asynhcronous commands and independent control of orientation and forward displacement. The middle layer is a control loop which maintins an estimate of the vehicle's position and orientation, as well as their uncertainties. The control loop generates estimates and commands translation and rotation in terms of a ‘virtual vehicle’. The bottom layer is a translator between the ‘virtual vehicle’ and whatever physical vehicle on which the controller is implemented.     

Intelligent Adaptive Motion Control Using Fuzzy Basis Function Networks for Electric Unicycle

This paper presents two intelligent adaptive controllers, called self‐balancing and speed controllers, for self‐balancing and motion control, respectively, of an electric unicycle using fuzzy basis function networks (FBFN), which are employed to approximate model uncertainties and unknown friction between the wheel and the terrain surface. Both controllers are established based on the linearized model of the vehicle whose model uncertainties and parameter variations are caused by different riders and terrain. An adaptive backstepping controller together with online learning FBFN and sensing information of the rider's body inclination then is presented to achieve self‐balancing motion control. By adding an electronic throttle as the input device of speed commands, a decoupling sliding‐mode controller with online learning FBFN is proposed to accomplish self‐balancing and speed control. The performance and merit of the two proposed control methods are exemplified by conducting four simulations and three experiments on a laboratory‐built electric unicycle.     

IMPLEMENTATION OF A DRIVING SIMULATOR BASED ON A STEWART PLATFORM AND COMPUTER GRAPHICS TECHNOLOGIES

This paper describes works related to the development of a land vehicle driving simulator, which consists of a Stewart platform as its motion device and a computer graphical system as its visual component. The main task is to enable the pilot‐experience the sensation of motion while driving the vehicle under the constraint of the platform's finite working space. Involved are works such as establishment of the vehicle dynamical model, analysis of the forces acting on the pilot, and application of the washout algorithm and human motion sensation models. With the results from these works, appropriate motion trajectory commands for the platform can be generated. Besides the physical motion part, a computer graphical system is installed to generate scenes that give visual cues. While following the pilot's steering signals and matching the platform's motion, the visual system creates animation scenes of the environment, which are shown on a large screen in front of the pilot through an LCD projector. To test the completed system, different pilots operate it and give subjective assessments. Also, gyros are mounted on the platform to measure its responses to motion commands. Here some experimental results are summarized and discussed.