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 A Path-Planning Performance Comparison of RRT*-AB with MEA* in a 2-Dimensional Environment

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 945 ◽  
Author(s):  
Iram Noreen ◽  
Amna Khan ◽  
Khurshid Asghar ◽  
Zulfiqar Habib
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Execution Time ◽  
Path Length ◽  
Optimal Path ◽  
Performance Comparison ◽  
Computational Time ◽  
And Performance ◽  
Commercial Applications ◽  
Space Requirements

With the advent of mobile robots in commercial applications, the problem of path-planning has acquired significant attention from the research community. An optimal path for a mobile robot is measured by various factors such as path length, collision-free space, execution time, and the total number of turns. MEA* is an efficient variation of A* for optimal path-planning of mobile robots. RRT*-AB is a sampling-based planner with rapid convergence rate, and improved time and space requirements than other sampling-based methods such as RRT*. The purpose of this paper is the review and performance comparison of these planners based on metrics, i.e., path length, execution time, and memory requirements. All planners are tested in structured and complex unstructured environments cluttered with obstacles. Performance plots and statistical analysis have shown that MEA* requires less memory and computational time than other planners. These advantages of MEA* make it suitable for off-line applications using small robots with constrained power and memory resources. Moreover, performance plots of path length of MEA* is comparable to RRT*-AB with less execution time in the 2D environment. However, RRT*-AB will outperform MEA* in high-dimensional problems because of its inherited suitability for complex problems.

Comparison between Waveform and Bug Path Planning Algorithm for Mobile Robot

2014 ◽  
Vol 607 ◽  
pp. 774-777
Author(s):  
Swee Ho Tang ◽  
Che Fai Yeong ◽  
Eileen Lee Ming Su
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Execution Time ◽  
Path Length ◽  
Simulation Software ◽  
Breadth First Search ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Grid Based

Mobile robots frequently find themselves in a circumstance where they need to find a trajectory to another position in their environment, subject to constraints postured by obstacles and the capabilities of the robot itself. This study compared path planning algorithms for mobile robots to move efficiently in a collision free grid based static environment. Two algorithms have been selected to do the comparison namely wavefront algorithm and bug algorithm. The wavefront algorithm involves a breadth-first search of the graph beginning at the goal position until it reaches the start position. The bug algorithm uses obstacles borders as guidance toward a goal with restricted details about the environment. The algorithms are compared in terms of parameters such as execution time of the algorithm and planned path length by using Player/Stage simulation software. Results shown that wavefront algorithm is a better path planning algorithm compared to bug algorithm in static environment.

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.

Utilization of the Oculus Rift HMD in Mobile Robot Teleoperation

2014 ◽  
Vol 555 ◽  
pp. 199-208 ◽  
Author(s):  
Tomáš Kot ◽  
Petr Novák
Keyword(s):  
User Interface ◽  
Remote Control ◽  
Mobile Robots ◽  
Graphical User Interface ◽  
Additional Data ◽  
Mobile Robotics ◽  
3D Display ◽  
Oculus Rift ◽  
Head Mounted Display ◽  
In The Beginning

This paper mentions some problems related to utilization of a head-mounted display (HMD) for remote control of mobile robots by a human operator and also presents a possible solution. Considered is specifically the new HMD device called Oculus Rift, which is a very interesting device because of its great parameters and low price. The device is described in the beginning, together with some of the specific principles of the Oculus 3D display. Then follows the design of a new graphical user interface for teleoperation, with main focus on visualization of stereoscopic images from robot cameras. Demonstrated is also a way how to display additional data and information to the operator. The overall aim is to create a comfortable and highly effective interface suitable both for exploration and manipulation tasks in mobile robotics.

scholarly journals MODIFIED VIRTUAL SEMI-CIRCLE PATH PLANNING

2016 ◽  
Vol 78 (6-6) ◽  
Author(s):  
R. N. Farah ◽  
Amira Shahirah ◽  
N. Irwan ◽  
R. L. Zuraida
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Optimal Path ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Reactive Navigation ◽  
Optimal Path Planning ◽  
Two Phases

The challenging part of path planning for an Unmanned Ground Vehicle (UGV) is to conduct a reactive navigation. Reactive navigation is implemented to the sensor based UGV. The UGV defined the environment by collecting the information to construct it path planning. The UGV in this research is known as Mobile Guard UGV-Truck for Surveillance (MG-TruckS). Modified Virtual Semi Circle (MVSC) helps the MG-TruckS to reach it predetermined goal point successfully without any collision. MVSC is divided into two phases which are obstacles detection phase and obstacles avoidance phase to compute an optimal path planning. MVSC produces shorter path length, smoothness of velocity and reach it predetermined goal point successfully.

Integrating Odor Sensing in Robotics

2018 ◽  
pp. 224-243
Author(s):  
Alauddin Yousif Al-Omary
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Chemical Sensors ◽  
Mobile Robotics ◽  
Future Research ◽  
Research Directions ◽  
The Future ◽  
The Status ◽  
Future Research Directions ◽  
Technical Challenges

In this chapter, the benefit of equipping the robot with odor sensors is investigated. The chapter addresses the types of tasks the mobile robots can accomplish with the help of olfactory sensing capabilities, the technical challenges in mobile robot olfaction, the status of mobile robot olfaction. The chapter also addresses simple and complex electronic olfaction sensors used in mobile robotics, the challenge of using chemical sensors, the use of many types of algorithms for robot olfaction, and the future research directions in the field of mobile robot olfaction.

Sign in / Sign up

Export Citation Format

Share Document