scholarly journals Optimal Path Smoothing with Log-aesthetic Curves Based on Shortest Distance, Minimum Bending Energy or Curvature Variation Energy

2019 ◽  
Vol 17 (3) ◽  
pp. 639-658 ◽  
Author(s):  
R. Gobithaasan ◽  
S. Yip ◽  
Kenjiro Miura ◽  
S. Madhavan
Keyword(s):  
Optimal Path ◽  
Bending Energy ◽  
Curvature Variation ◽  
Shortest Distance ◽  
Path Smoothing

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 Collision Free Smooth Path for Mobile Robots in Cluttered Environment Using an Economical Clamped Cubic B-Spline

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1567
Author(s):  
Iram Noreen
Keyword(s):  
Mobile Robots ◽  
Execution Time ◽  
Path Length ◽  
Mobile Robotics ◽  
Optimal Path ◽  
Post Processing ◽  
B Spline ◽  
Smooth Path ◽  
Path Smoothing ◽  
Narrow Passage

Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such as path length, path smoothness, collision-free curve, execution time, and the total number of turns. However, most of the planners generate a non-smooth less optimal and linear piecewise path. Post processing smoothing is applied at the cost of increase in path length. Moreover, current research on post-processing path smoothing techniques does not address the issues of post smoothness collision and performance efficiency. This paper presents a path smoothing approach based on clamped cubic B-Spline to resolve the aforementioned issues. The proposed approach has introduced an economical point insertion scheme with automated knot vector generation while eliminating post smoothness collisions with obstacles. It generates C2 continuous path without any stitching point and passes more closely to the originally planned path. Experiments and comparison with previous approaches have shown that the proposed approach generates better results with reduced path length, and execution time. The test cases used for experiments include a simple structure environment, complex un-structured environment, an environment full of random cluttered narrow obstacles, and a case study of an indoor narrow passage.

scholarly journals Route Choice of the Shortest Travel Time Based on Floating Car Data

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Jingwei Shen ◽  
Yifang Ban
Keyword(s):  
Travel Time ◽  
Optimal Path ◽  
Route Choice ◽  
Edge Weight ◽  
Map Matching ◽  
Traffic Condition ◽  
Floating Car Data ◽  
Road Map ◽  
Shortest Distance ◽  
Comparison Results

Finding a route with shortest travel time according to the traffic condition can help travelers to make better route choice decisions. In this paper, the shortest travel time based on FCD (floating car data) which is used to assess overall traffic conditions is proposed. To better fit FCD and road map, a new map matching algorithm which fully considers distance factor, direction factor, and accessibility factor is designed to map all GPS (Global Positioning System) points to roads. A mixed graph structure is constructed and a route analysis algorithm of shortest travel time which considers the dynamic edge weight is designed. By comparing with other map matching algorithms, the proposed method has a higher accuracy. The comparison results show that the shortest travel time path is longer than the shortest distance path, but it costs less traveling time. The implementation of the route choice based on the shortest travel time method can be used to guide people’s travel by selecting the space-time dependent optimal path.

scholarly journals Multi-Objective Shortest Path Model for Optimal Route between Commercial Cities on America

2019 ◽  
pp. 1394-1403
Author(s):  
Mohammed S. Ibrahim
Keyword(s):  
Shortest Path ◽  
Transportation Network ◽  
Optimal Path ◽  
Path Model ◽  
Multi Objective ◽  
Proposed Model ◽  
Shortest Distance ◽  
Lexicographic Method ◽  
Package Program ◽  
Us Cities

The traditional shortest path problem is mainly concerned with identifying the associated paths in the transportation network that represent the shortest distance between the source and the destination in the transportation network by finding either cost or distance. As for the problem of research under study it is to find the shortest optimal path of multi-objective (cost, distance and time) at the same time has been clarified through the application of a proposed practical model of the problem of multi-objective shortest path to solve the problem of the most important 25 commercial US cities by travel in the car or plane. The proposed model was also solved using the lexicographic method through package program Win-QSB 2.0 for operational research applications.

scholarly journals Smart element aware gate controller for intelligent wheeled robot navigation

2021 ◽  
Vol 11 (4) ◽  
pp. 3022
Author(s):  
Nadia Adnan Shiltagh Al-Jamali ◽  
Mahmood Z. Abdullah
Keyword(s):  
Mobile Robot ◽  
Optimal Path ◽  
Maximum Velocity ◽  
Elman Neural Network ◽  
Indoor Mobile Robot ◽  
Shortest Distance ◽  
Wheeled Robot ◽  
Physical Barriers ◽  
Neuro Controller ◽  
Better Than

<p>The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.</p>

scholarly journals IMPLEMENTASI ALGORITMA DIJKSTRA UNTUK MENENTUKAN JALUR TERPENDEK DALAM DISTRIBUSI BARANG

2021 ◽  
Vol 2 (2) ◽  
pp. 194-203
Author(s):  
Ikhsan Baharudin ◽  
Ahmad Jaka Purwanto ◽  
Teguh Rahayu Budiman ◽  
Muchammad Fauzi
Keyword(s):  
Shortest Path ◽  
Manufacturing Industry ◽  
Optimal Path ◽  
Transportation Costs ◽  
Project Work ◽  
Shortest Route ◽  
Regular Customer ◽  
Shortest Distance ◽  
The Cost ◽  
A Company

PT. X is a company domiciled in Gedebage, Bandung which is engaged in the manufacturing industry by producing precision parts using CNC machines. PT. X is a sub-contracting company that usually serves project work from other companies. PT. Y and PT. Z is a regular customer who often works with PT. X. So that PT. X often sends finished products directly to PT. Y who is domiciled on Jl. Gatot Subroto, Bandung and also PT. Z who is domiciled on Jl. Pajajaran, Bandung. To minimize the cost of distribution of goods, PT. X must determine an adequate path taking into account the optimization of transportation costs. One of the variables that affect transportation costs is distance. It is assumed that the optimal path for transportation costs is the shortest distance using the Dijkstra method. This test uses data from Google Maps to find out the distance to each destination, making it easier to get the shortest path. Obtained the shortest path from PT. X to PT.Y is 12.3 Km via West Java Police then Carefour, while the shortest route is from PT. Y to PT. Z is 10.7 Km via Simpang Lima then Vie Hotel Westhoff. So that the optimal total mileage for distributing goods is 23 Km.

Method of localization of agricultural robotic vehicles using AESA established by an UAV complex

2021 ◽  
Vol 9 (2) ◽  
pp. 112-120
Author(s):  
Aleksandr Denisov
Keyword(s):  
Noise Immunity ◽  
Phase Shifter ◽  
Optimal Path ◽  
Weather Conditions ◽  
Night Time ◽  
Shortest Distance ◽  
Wide Range ◽  
Electronically Scanned Arrays ◽  
Time Required ◽  
Agricultural Areas

This paper considers a relevant method to ensure communication and object location in vast agricultural areas. To solve this problem an operational scenario was proposed, an approach, involving a complex of several UAVs, which establish an AESA; an algorithm for building an optimal path, along which the UAV complex moves, formulas for calculating AESA direction pattern for linear and flat formations of UAV groups, formulas for calculating time, required for terrain scanning with various areas. In such complex on each UAV an antenna with phase shifter is mounted. The paper also considers modeling and comparison of different approaches to motion of an UAV complex for terrain scanning. Due to application of active electronically scanned arrays, the proposed localization method is characterized by high noise immunity, is better shielded from noise, less dependent on weather conditions and appliable at night time. Unlike other methods, it supports wide-range transmission and reception of data. Thereby, application of AESA makes this method robust and practical for localization and communication establishment, whereas the proposed algorithm for building of optimal path, along which the robotic complex moves, enables to reduce time, required for area scanning. Consequently, this method allows achieving the shortest distance that the UAV complex has to cover.

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