New interpretation of fractional potential fields for robust path planning

2019 ◽  
Vol 22 (1) ◽  
pp. 113-127 ◽  
Author(s):  
Jean-Baptiste Receveur ◽  
Stéphane Victor ◽  
Pierre Melchior
Keyword(s):  
Path Planning ◽  
Autonomous Vehicles ◽  
Control Method ◽  
Methodological Approach ◽  
Potential Fields ◽  
Attractive Potential ◽  
On Line ◽  
New Interpretation ◽  
Definition Of ◽  
Intermediate Targets

Abstract Trajectory planning for autonomous vehicles is a research topical subject. In previous studies, optimal intermediate targets have been used in the Potential Fields (PFs). PFs are only a path planning method, or a reactive obstacle avoidance method and not a trajectory tracking method. In this article, the PFs are interpreted as an on-line control method to follow an optimal trajectory. An analysis and methodological approach to design the attractive potential as a robust controller are proposed, and a new definition of a fractional repulsive potential to characterize the dangerousness of obstacles is developed. Simulation results on autonomous vehicles are given.

scholarly journals Path planning with fractional potential fields for autonomous vehicles

2017 ◽  
Vol 50 (1) ◽  
pp. 14533-14538 ◽  
Author(s):  
Julien Moreau ◽  
Pierre Melchior ◽  
Stéphane Victor ◽  
François Aioun ◽  
Franck Guillemard
Keyword(s):  
Path Planning ◽  
Autonomous Vehicles ◽  
Potential Fields

scholarly journals Path Planning for Autonomous Vehicles Using QZSS and Satellite Visibility Map

2013 ◽  
Vol 25 (2) ◽  
pp. 400-407 ◽  
Author(s):  
Mitsunori Kitamura ◽  
◽  
Yoichi Yasuoka ◽  
Taro Suzuki ◽  
Yoshiharu Amano ◽  
...  
Keyword(s):  
Path Planning ◽  
Autonomous Vehicles ◽  
Dead Reckoning ◽  
Path Following ◽  
Planning Method ◽  
Self Control ◽  
Potential Fields ◽  
Visibility Map ◽  
Gps Satellites ◽  
Satellite Visibility

This paper describes a path planning method that uses the Quasi-Zenith Satellites System(QZSS) and a satellite visibility map for autonomous vehicles. QZSS is a positioning system operated by Japan that has an effect similar to an increase in the number of GPS satellites. Therefore, QZSS can be used to improve the availability of GPS positioning. A satellite visibility map is a special map that simulates the number of visible satellites at all points on the map. The vehicle can use the satellite visibility map to determine the points that receive more satellite signals. The proposed method generates the artificial potential fields from the satellite visibility map and obstacle information around the vehicle, and it generates the path following the potential fields. Thereby, the vehicle can select the path that has more satellite signals, improving the availability of GPS fixed solutions. Hence, the vehicle can reduce the accumulated error by dead reckoning, and it can improve the safety of self-control. In this study, we evaluate the satellite visibility maps and the path planning method. The results show that the proposed method does improve the availability of GPS fixed solutions.

Identification of managerial competencies of the organizational leaders of the Passifloraceae production sector in the Huila Department

2020 ◽  
Vol 36 (67) ◽  
pp. 61-78
Author(s):  
Hernando Gil Tovar ◽  
Derly Cibelly Lara Figueroa
Keyword(s):  
Methodological Approach ◽  
Superior Performance ◽  
Organizational Leaders ◽  
Management Skills ◽  
Generational Change ◽  
Production Sector ◽  
Managerial Competencies ◽  
Conducting Research ◽  
Definition Of ◽  
Small Producers

Managerial competencies, defined as the “underlying characteristics of an individual that have a causal relationship with effective or superior performance in the job” (Boyatzis, 1982, p. 12), are key to achievement of productive purposes in the Huila department, in Colombia. The present article, as an investigative result, seeks to identify those managerial competencies, both current and required, of the organizational leaders in the Passifloraceae productive sector in the Huila department, in Colombia. The epistemological paradigm used in this article is that of interpretivism. The reasoning method is deductive, and the methodological approach is mixed. The unit of analysis for this study consists of the directors of the associative organizations of Passifloraceae producers in the productive chain, where two types of players are identified: thirteen (13) leaders of organizations producing passion fruit, and five (5) representatives of institutions in the Huila department that influence the sector. The study concludes with the definition of the map of current managerial competences of organizations in the passionfruit productive sector, and is then contrasted with the map of competences required from these. It also highlights the importance of associativity for small producers, the need to continue conducting research in the sector, and the need to intervene through social outreach projects, so as to generate appropriation and training processes for a set of managerial competencies identified herein, which will strengthen management skills and competitiveness in this type of organization, and ensure, over time, generational change within the sector.

Two Theories of Effective Government

2017 ◽  
Author(s):  
Johannes Lindvall
Keyword(s):  
Political Science ◽  
Political Institutions ◽  
Public Policies ◽  
Methodological Approach ◽  
Decision Makers ◽  
Precise Definition ◽  
Policy Changes ◽  
Political Decision ◽  
Definition Of ◽  
The Relationship

This chapter introduces the problem of “reform capacity” (the ability of political decision-makers to adopt and implement policy changes that benefit society as a whole, by adjusting public policies to changing economic, social, and political circumstances). The chapter also reviews the long-standing discussion in political science about the relationship between political institutions and effective government. Furthermore, the chapter explains why the possibility of compensation matters greatly for the politics of reform; provides a precise definition of the concept of reform capacity; describes the book's general approach to this problem; and discusses the ethics of compensating losers from reform; and presents the book's methodological approach.

The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

2021 ◽  
pp. 095440702110090
Author(s):  
Xing Xu ◽  
Minglei Li ◽  
Feng Wang ◽  
Ju Xie ◽  
Xiaohan Wu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Control Method ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Test Track ◽  
Optimal Control Method ◽  
The Future ◽  
On The Road

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

scholarly journals Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2244
Author(s):  
S. M. Yang ◽  
Y. A. Lin
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Random Trees ◽  
Average Deviation ◽  
Lane Changes ◽  
Path Smoothing ◽  
Rapidly Exploring Random Trees

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

scholarly journals Task-space regulation of rigid-link electrically-driven robots with uncertain kinematics using neural networks

2021 ◽  
Vol 54 (1-2) ◽  
pp. 102-115
Author(s):  
Wenhui Si ◽  
Lingyan Zhao ◽  
Jianping Wei ◽  
Zhiguang Guan
Keyword(s):  
Neural Networks ◽  
Asymptotic Stability ◽  
Control Method ◽  
Joint Space ◽  
Robot Kinematics ◽  
Rbf Neural Networks ◽  
Task Space ◽  
Actuator Dynamics ◽  
Rigid Link ◽  
On Line

Extensive research efforts have been made to address the motion control of rigid-link electrically-driven (RLED) robots in literature. However, most existing results were designed in joint space and need to be converted to task space as more and more control tasks are defined in their operational space. In this work, the direct task-space regulation of RLED robots with uncertain kinematics is studied by using neural networks (NN) technique. Radial basis function (RBF) neural networks are used to estimate complicated and calibration heavy robot kinematics and dynamics. The NN weights are updated on-line through two adaptation laws without the necessity of off-line training. Compared with most existing NN-based robot control results, the novelty of the proposed method lies in that asymptotic stability of the overall system can be achieved instead of just uniformly ultimately bounded (UUB) stability. Moreover, the proposed control method can tolerate not only the actuator dynamics uncertainty but also the uncertainty in robot kinematics by adopting an adaptive Jacobian matrix. The asymptotic stability of the overall system is proven rigorously through Lyapunov analysis. Numerical studies have been carried out to verify efficiency of the proposed method.

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