Trajectory Tracking of 3D Autonomous Vehicles Using Backstepping Control

2019 ◽  
Author(s):  
Karl Ludwig Fetzer ◽  
Sergey G. Nersesov ◽  
Hashem Ashrafiuon
Keyword(s):  
Autonomous Vehicles ◽  
Degrees Of Freedom ◽  
3D Model ◽  
Autonomous Vehicle ◽  
Backstepping Control ◽  
Reference Trajectory ◽  
Control Laws ◽  
Six Degrees Of Freedom ◽  
Error Dynamics ◽  
Dynamics Stability

Abstract In this paper, the authors derive backstepping control laws for tracking a time-based reference trajectory for a 3D model of an autonomous vehicle with two degrees of underactuation. Tracking all six degrees of freedom is made possible by a transformation that reduces the order of the error dynamics. Stability of the resulting error dynamics is proven and demonstrated in simulations.

Experiments on Linear and Nonlinear Control of a Multi-DOF Parallel Mechanism

2003 ◽  
Author(s):  
Sandor Riebe ◽  
Heinz Ulbrich
Keyword(s):  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Parallel Robot ◽  
Parallel Kinematics ◽  
Control Laws ◽  
Six Degrees Of Freedom ◽  
Position Accuracy ◽  
Nonlinear Approach ◽  
Linear Approach ◽  
Measurement Results

Parallel kinematics with multi degrees-of-freedom (DOF), like hexapod-systems, are mostly used in applications where high demands on position accuracy are required and/or high accelerations are needed. Adequate control concepts are essential in order to achieve the desired dynamic response. This paper deals with a comparative study of two structural different control concepts applied on a parallel robot with six degrees-of-freedom. The first one is a decentral linear approach and the second one is a multivariable nonlinear approach. The two concepts are presented and implemented on an experimental hexapod-system. In order to verify the used dynamic model comparisons between simulation and measurement results are shown. Finally, experiments have been carried out to compare the control laws with respect to their motion tracking performance.

Can we Localize an AV from a Single Image? Deep-Geometric 6 DoF Localization in Topo-metric Maps

2021 ◽  
pp. 1-13
Author(s):  
Punarjay Chakravarty ◽  
Tom Roussel ◽  
Gaurav Pandey ◽  
Tinne Tuytelaars
Keyword(s):  
Pose Estimation ◽  
Autonomous Vehicles ◽  
Hybrid Algorithm ◽  
Degrees Of Freedom ◽  
Single Camera ◽  
Single Image ◽  
Six Degrees Of Freedom ◽  
Localization Algorithms ◽  
Mapping Process ◽  
Set Of Points

Abstract We describe a Deep-Geometric Localizer that is able to estimate the full six degrees-of-freedom (DoF) global pose of the camera from a single image in a previously mapped environment. Our map is a topo-metric one, with discrete topological nodes whose 6DOF poses are known. Each topo-node in our map also comprises of a set of points, whose 2D features and 3D locations are stored as part of the mapping process. For the mapping phase, we utilise a stereo camera and a regular stereo visual SLAM pipeline. During the localization phase, we take a single camera image, localize it to a topological node using Deep Learning, and use a geometric algorithm (PnP) on the matched 2D features (and their 3D positions in the topo map) to determine the full 6DOF globally consistent pose of the camera. Our method divorces the mapping and the localization algorithms and sensors (stereo and mono), and allows accurate 6DOF pose estimation in a previously mapped environment using a single camera. With results in simulated and real environments, our hybrid algorithm is particularly useful for autonomous vehicles (AVs) and shuttles that might repeatedly traverse the same route.

scholarly journals Integrated Avoid Collision Control of Autonomous Vehicle Based on Trajectory Re-Planning and V2V Information Interaction

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1079 ◽  
Author(s):  
Fen Lin ◽  
Kaizheng Wang ◽  
Youqun Zhao ◽  
Shaobo Wang
Keyword(s):  
Autonomous Vehicles ◽  
Control Method ◽  
Integrated Control ◽  
Autonomous Vehicle ◽  
Longitudinal Velocity ◽  
Reference Trajectory ◽  
Threshold Method ◽  
Lane Changing ◽  
Information Interaction ◽  
Fitting In

An integrated longitudinal-lateral control method is proposed for autonomous vehicle trajectory tracking and dynamic collision avoidance. A method of obstacle trajectory prediction is proposed, in which the trajectory of the obstacle is predicted and the dynamic solution of the reference trajectory is realized. Aiming at the lane changing scene of autonomous vehicles driving in the same direction and adjacent lanes, a trajectory re-planning motion controller with the penalty function is designed. The reference trajectory parameterized output of local reprogramming is realized by using the method of curve fitting. In the framework of integrated control, Fuzzy adaptive (proportional-integral) PI controller is proposed for longitudinal velocity tracking. The selection and control of controller and velocity are realized by logical threshold method; A model predictive control (MPC) with vehicle-to-vehicle (V2V) information interaction modular and the driver characteristics is proposed for direction control. According to the control target, the objective function and constraints of the controller are designed. The proposed method’s performance in different scenarios is verified by simulation. The results show that the autonomous vehicles can avoid collision and have good stability.

Coupling in-flight trajectory planning and flocking for multiple autonomous parafoils

2012 ◽  
Vol 226 (6) ◽  
pp. 691-720 ◽  
Author(s):  
A Rosich ◽  
P Gurfil
Keyword(s):  
Global Positioning System ◽  
Autonomous Navigation ◽  
Degrees Of Freedom ◽  
Reference Trajectory ◽  
Flight Trajectory ◽  
Multiagent Simulation ◽  
Six Degrees Of Freedom ◽  
Wide Range ◽  
Global Positioning ◽  
Simple Rules

Much effort has been invested during the past decades in design of parafoils for a wide range of payloads and in development of means for their guidance. Existing parafoils are capable of autonomous navigation using the global positioning system and other onboard sensors. The purpose of this study is to explore the advantages of coordination among multiple autonomous parafoils. Each parafoil is able to navigate to the target on its own by following a real-time-generated reference trajectory. A new method for trajectory generation is presented and behaviour-based rules are developed that control the relative motion of the descending parafoils. The set of simple rules results in an emergent behaviour known as flocking. The coupling between trajectory following and flocking is studied in a multiagent simulation. The simulation uses a realistic six-degrees-of-freedom model of a heavy cargo parafoil. The obtained results demonstrate the possibility of flocking behaviour for guided parafoils. The flocking rules ensure safe separation between the vehicles headed for the same target and allow the parafoils to follow a reference trajectory as a group.

Inverse Kinematics Simulation for a Surgical Robot Using CATIA

2015 ◽  
Vol 780 ◽  
pp. 49-54
Author(s):  
Shao Gang Liu ◽  
Edris Farah
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
3D Model ◽  
Geometric Approach ◽  
Surgical Robot ◽  
Six Degrees Of Freedom ◽  
Kinematics Simulation ◽  
Kinematics Modeling ◽  
Model Equations ◽  
The Mathematical Model

Robotic arm with six degrees of freedom can be successfully used to do a surgical task through a small incision called (RCM point) on the patient's body. Inverse Kinematics modeling and simulating of a 6 DOF surgical robot is developed in this paper. The mathematical model equations are built using geometric approach and the Denavit-Hartenberg convention. The 3D model of the robot is created by CATIA5 to simulate the motion of the robot in surgical environments. The inverse kinematics equations model is validated through the simulating model. Result confirms that the proposed robot mechanism is applicable for minimally invasive surgery applications.

Control Laws synthesis of multi-arm cooperating robots with elastic interconnection at the contacts

Robotica ◽  
2000 ◽  
Vol 18 (2) ◽  
pp. 183-193 ◽  
Author(s):  
Milovan Zˇivanović ◽  
Miomir Vukobratović
Keyword(s):  
Theoretical Analysis ◽  
Degrees Of Freedom ◽  
Closed Loop ◽  
Cooperative System ◽  
Controlled System ◽  
Control Laws ◽  
Cooperative Manipulation ◽  
Six Degrees Of Freedom ◽  
Cooperating Robots

The problem of the control of the object cooperative manipulation during the work of multiple non-redundant six degrees-of-freedom manipulators is considered in this paper. The problem of the cooperative manipulation control is, like all its problems, solvable only if the system is considered as the elastic one, taking into account all existing constraints. The controlled system is with the output number greater than the available number of inputs, therefore, in the first stage the desired motions are selected from the set of the possible nominal ones, containing the trajectories of the manipulated object mass centre and slave manipulators contacts. Afterward, the classification of control tasks is performed. The procedure for the calculation of the driving torques introduced into the joints of the manipulators, necessary to obtain the nominal trajectory tracking, is proposed. The theoretical analysis of cooperative system closed loop behaviour is exposed, particular attention being paid to the uncontrolled variables. The procedure is illustrated on the example of the simple closed loop cooperative system, consisting of the manipulated object and two one degree-of-freedom manipulators. For this system, the behaviour is determined and the driving torques are calculated.

scholarly journals CFNet: LiDAR-Camera Registration Using Calibration Flow Network

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8112
Author(s):  
Xudong Lv ◽  
Shuo Wang ◽  
Dong Ye
Keyword(s):  
Autonomous Vehicles ◽  
Degrees Of Freedom ◽  
Image Data ◽  
Ground Truth ◽  
Geometric Information ◽  
Six Degrees Of Freedom ◽  
Calibration Methods ◽  
Extrinsic Parameters ◽  
Calibration Algorithm ◽  
Complex Optimization

As an essential procedure of data fusion, LiDAR-camera calibration is critical for autonomous vehicles and robot navigation. Most calibration methods require laborious manual work, complicated environmental settings, and specific calibration targets. The targetless methods are based on some complex optimization workflow, which is time-consuming and requires prior information. Convolutional neural networks (CNNs) can regress the six degrees of freedom (6-DOF) extrinsic parameters from raw LiDAR and image data. However, these CNN-based methods just learn the representations of the projected LiDAR and image and ignore the correspondences at different locations. The performances of these CNN-based methods are unsatisfactory and worse than those of non-CNN methods. In this paper, we propose a novel CNN-based LiDAR-camera extrinsic calibration algorithm named CFNet. We first decided that a correlation layer should be used to provide matching capabilities explicitly. Then, we innovatively defined calibration flow to illustrate the deviation of the initial projection from the ground truth. Instead of directly predicting the extrinsic parameters, we utilize CFNet to predict the calibration flow. The efficient Perspective-n-Point (EPnP) algorithm within the RANdom SAmple Consensus (RANSAC) scheme is applied to estimate the extrinsic parameters with 2D–3D correspondences constructed by the calibration flow. Due to its consideration of the geometric information, our proposed method performed better than the state-of-the-art CNN-based methods on the KITTI datasets. Furthermore, we also tested the flexibility of our approach on the KITTI360 datasets.

BACKSTEPPING CONTROL STRATEGY FOR AN UNDERACTUATED X4-AUV

2015 ◽  
Vol 74 (9) ◽  
Author(s):  
Zainah Md. Zain ◽  
Nur Fadzillah Harun
Keyword(s):  
Nonlinear Control ◽  
Lyapunov Stability ◽  
Control Strategy ◽  
Stability Theory ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Lyapunov Stability Theory ◽  
Backstepping Control ◽  
Six Degrees Of Freedom ◽  
Nonlinear Control Method

A nonlinear control method is considered for stabilizing all attitudes and positions (x, y or z) of an underactuated X4-AUV with four thrusters and six degrees-of-freedom (DOFs), in which the positions are stabilized according to the Lyapunov stability theory and angles are stabilized using backstepping control method. A dynamical model is first derived, and then a sequential nonlinear control strategy is implemented for the X4-AUV, composed of translational and rotational subsystems. A controller for the translational subsystem stabilizes one position out of x-, y-, and z-coordinates, whereas controllers for the rotational subsystems generate the desired roll, pitch and yaw angles. Thus, the rotational controllers stabilize all the attitudes of the X4-AUV at a desired (x-, y- or z-) position of the vehicle. Some numerical simulations are conducted to demonstrate the effectiveness of the proposed controllers.

scholarly journals IPS – a vision aided navigation system

2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Anko Börner ◽  
Dirk Baumbach ◽  
Maximilian Buder ◽  
Andre Choinowski ◽  
Ines Ernst ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Degrees Of Freedom ◽  
Local Coordinate System ◽  
Human Head ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Six Degrees Of Freedom ◽  
Measurement Systems ◽  
External Reference ◽  
German Aerospace

AbstractEgo localization is an important prerequisite for several scientific, commercial, and statutory tasks. Only by knowing one’s own position, can guidance be provided, inspections be executed, and autonomous vehicles be operated. Localization becomes challenging if satellite-based navigation systems are not available, or data quality is not sufficient. To overcome this problem, a team of the German Aerospace Center (DLR) developed a multi-sensor system based on the human head and its navigation sensors – the eyes and the vestibular system. This system is called integrated positioning system (IPS) and contains a stereo camera and an inertial measurement unit for determining an ego pose in six degrees of freedom in a local coordinate system. IPS is able to operate in real time and can be applied for indoor and outdoor scenarios without any external reference or prior knowledge. In this paper, the system and its key hardware and software components are introduced. The main issues during the development of such complex multi-sensor measurement systems are identified and discussed, and the performance of this technology is demonstrated. The developer team started from scratch and transfers this technology into a commercial product right now. The paper finishes with an outlook.

scholarly journals Analysis of the Impact of the Target Illumination Time on the Effectiveness of the Flight Trajectory Correction System

2019 ◽  
Vol 49 (1) ◽  
pp. 229-253
Author(s):  
Grzegorz Kowaleczko ◽  
Mariusz Pietraszek ◽  
Łukasz Słonkiewicz
Keyword(s):  
Degrees Of Freedom ◽  
Flight Trajectory ◽  
Control Laws ◽  
Illumination Time ◽  
Six Degrees Of Freedom ◽  
Laser Sensors ◽  
Main Factors ◽  
The Impact ◽  
Flight Simulations ◽  
Correction System

Abstract This paper presents method of flight simulations for released laser guided bomb. Calculations were performed using six-degrees-of-freedom mathematical model of a bomb motion. Aerodynamics of the bomb was calculated using commercial software. Control laws were determined on the basis of signals detected by two pairs of laser sensors. Exemplary results of numerical calculations are submitted and conclusions focused on the main factors influencing on bombing accuracy are shown.

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