Spatial Path Tracking Controllers for Autonomous Ground Vehicles: Conventional and Nonconventional Schemes

2021 ◽  
Vol 01 (01) ◽  
pp. 2150003
Author(s):  
Peng Wang ◽  
Di An ◽  
Ning Chen ◽  
Yang Quan Chen
Keyword(s):  
Path Tracking ◽  
Spatial Distance ◽  
Ground Vehicles ◽  
Control Laws ◽  
Tracking Controllers ◽  
Tracking Controller ◽  
Different Types ◽  
Proportional Controller ◽  
Optimization Search ◽  
Fractional Order Integral

Unlike time-based path tracking controllers, the [Formula: see text]-controller is a spatial path tracking controller. It is a purely geometric path tracking controller and essentially a P-controller to maintain the reasonable spatial distance, [Formula: see text], from the vehicle to the desired path. In this paper, we present some enhancement schemes using the non-conventional PI control laws via optimization. We propose to use a nonlinear term [Formula: see text] for the proportional controller. A fractional-order integral used to achieve a PI[Formula: see text] control. Among the schemes, an optimization search procedure applied to find optimal controller gains by meshing the regions around the values from approximate linear designs. The performance index for parametric optimization is the integration of the absolute purely spatial deviation from the desired path. Three different types of road shape were chosen and the Gazebo-ROS simulation results were presented to show the effectiveness of the proposed enhancement schemes. The results show that in some cases a smaller [Formula: see text] and [Formula: see text] can be achieved by using [Formula: see text] controller, but its disadvantage is there may be some oscillation. For PI[Formula: see text] controller, there is an additional adjustable parameter [Formula: see text], better performance can be achieved without significant disadvantages which is worth in-depth research.

Ground Transport for an Air Organisation

1928 ◽  
Vol 32 (211) ◽  
pp. 596-623 ◽  
Author(s):  
R. E. H. Allen
Keyword(s):  
British Empire ◽  
Air Force ◽  
Similar Magnitude ◽  
Ground Vehicles ◽  
Royal Air Force ◽  
Different Types ◽  
Aerial Transport ◽  
Different Parts

Probably few realise that a self–contained organisation for maintaining an air fleet would need many more different types of ground vehicles than aircraft. This is true in the case of the Royal Air Force even if all vehicles of a purely military nature are excluded. It is highly probable that a civilian air organisation of similar magnitude would have fewer types of aircraft, but if it were to be self–contained and operate in different parts of the globe, it could not do with many less types of ground vehicles than the R.A.F. finds necessary.Obviously this depends on the interpretation of the term “self–contained.” Most of the small aerial transport companies have their own ground transport organisations, but they are far from being self–contained in the sense in which the author wishes to use the term to–night. We would all like to see a vast civilian air organisation operating in and between all the different units which comprise the British Empire. Nothing would do more to knit us and the Dominions and Colonies into one impregnable whole.

Control of Elastic Systems via Passivity-Based Methods

2004 ◽  
Vol 10 (11) ◽  
pp. 1699-1735 ◽  
Author(s):  
A. G. Kelkar ◽  
S. M. Joshi
Keyword(s):  
Flexible Structures ◽  
Robotic Manipulators ◽  
Mathematical Concept ◽  
Controller Synthesis ◽  
Control Laws ◽  
Linear Elastic ◽  
Elastic Systems ◽  
Different Types ◽  
Linear Controllers ◽  
Synthesis Approach

In this paper we present a controller synthesis approach for elastic systems based on the mathematical concept of passivity. For nonlinear and linear elastic systems that are inherently passive, robust control laws are presented that guarantee stability. Examples of such systems include flexible structures with col-located and compatible actuators and sensors, and multibody space-based robotic manipulators. For linear elastic systems that are not inherently passive, methods are presented for rendering them passive by compensation. The “passified” systems can then be robustly controlled by a class of passive linear controllers that guarantee stability despite uncertainties and inaccuracies in the mathematical models. The controller synthesis approach is demonstrated by application to five different types of elastic systems.

Active Disturbance Rejection Control for Handling Slip in Tracked Vehicle Locomotion

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Bijo Sebastian ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Disturbance Rejection ◽  
Path Tracking ◽  
Future Research ◽  
Ground Vehicles ◽  
Uneven Terrain ◽  
Active Disturbance Rejection ◽  
Package Delivery ◽  
Disturbance Rejection Control ◽  
Effective Slip ◽  
High Level

This paper describes the use of an active disturbance rejection controller (ADRC) to estimate and compensate for the effect of slip in an online manner to improve the path tracking performance of autonomous ground vehicles (AGVs). AGVs with skid-steer locomotion mode are extensively used for robotic applications in the fields of agriculture, transportation, construction, warehouse maintenance, and mining. Majority of these applications such as performing reconnaissance and rescue operations in rough terrain or autonomous package delivery in urban scenarios, require the system to follow a path predetermined by a high-level planner or based on a predefined task. In the absence of effective slip estimation and compensation, the AGVs, especially tracked vehicles, can fail to follow the path as given out by the high-level planner. The proposed ADRC architecture uses a generic mathematical model that can account for the scaling and shift in the states of the system due to the effects of slip through augmented parameters. An extended Kalman filter (EKF) observer is used to estimate the varying slip parameters online. The estimated parameters are then used to compensate for the effects of slip at each iteration by modifying the control actions given by a low-level path tracking controller. The proposed approach is validated through experiments over flat and uneven terrain conditions including asphalt, vinyl flooring, artificial turf, grass, and gravel using a tracked skid-steer mobile robot. A detailed discussion on the results and directions for future research is also presented.

scholarly journals Path tracking controller design for autonomous vehicle based on robust tube MPC

2020 ◽  
Vol 82 (1/2/3/4) ◽  
pp. 120
Author(s):  
Han Dong ◽  
Xin Zhang ◽  
Cong Geng ◽  
Chuanyang Sun
Keyword(s):  
Controller Design ◽  
Autonomous Vehicle ◽  
Path Tracking ◽  
Tracking Controller

scholarly journals A BOUNDARY-ENHANCED SUPERVOXEL METHOD FOR EXTRACTION OF ROAD EDGES IN MLS POINT CLOUDS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 65-71
Author(s):  
Z. Sha ◽  
Y. Chen ◽  
W. Li ◽  
C. Wang ◽  
A. Nurunnabi ◽  
...  
Keyword(s):  
Point Clouds ◽  
Drop Out ◽  
Spatial Distance ◽  
Road Extraction ◽  
High Definition ◽  
Geometric Information ◽  
3D Point Clouds ◽  
Different Types ◽  
Promising Solution ◽  
Normal Feature

Abstract. Road extraction plays a significant role in production of high definition maps (HD maps). This paper presents a novel boundary-enhanced supervoxel segmentation method for extracting road edge contours from MLS point clouds. The proposed method first leverages normal feature judgment to obtain 3D point clouds global geometric information, then clusters points according to an existing method with global geometric information to enhance the boundaries. Finally, it utilizes the neighbor spatial distance metric to extract the contours and drop out existing outliers. The proposed method is tested on two datasets acquired by a RIEGL VMX-450 MLS system that contain the major point cloud scenes with different types of road boundaries. The experimental results demonstrate that the proposed method provides a promising solution for extracting contours efficiently and completely. Results show that the precision values are 1.5 times higher and approximately equal than the other two existing methods when the recall value is 0 for both tested two road datasets.

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