waypointContolForPa​thPlanningTWMCS()

Version 1.5.0.0 (7.77 KB) by Srikanth Kandanuru Venkata Sudarshan
Path planning algorithm using gradient-descent on way-points to cover interesting regions
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Updated 18 May 2015

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Using a robot to recharge batteries and transfer data can dramatically increase the lifespan of a wireless sensor network. In this video, the path of the robot is controlled by waypoints (green circles), and the regions where each sensor can be serviced are highlighted. We use a combination of gradient descent and a 'multiple-traveling salesman problem' (mTSP) search algorithm to move the waypoints toward regions where sensor nodes can be recharged while ensuring waypoints stay close together.
Srikanth K. V. Sudarshan and Aaron T. Becker, presented Apr. 24 at the "2015 Texas Symposium on Wireless Microwave circuits and Systems" conference at Baylor University.
http://texassymposium.org/

"Designing Paths to Sustain Wireless Sensor Networks"
ABSTRACT: A structural-health wireless sensor network (WSN) should last for decades, but traditional disposable batteries cannot sustain such a network. Energy is the major impediment to sustainability of WSNs. Most energy is consumed by (i) wireless transmissions of perceived data, and (ii) long-distance multi-hop transmissions from the source sensors to the sink. This paper explores how to exploit emerging wireless power transfer technology by using robotic unmanned vehicles (UVs) to service the WSNs. These UVs cut data transmissions from long to short-distances, collect sensed information, and replenish WSN's energy.
This paper presents path-planning and path optimization algorithms for sustaining WSNs.

One robot: http://youtu.be/PxvbBEYNc7I
Four robots: http://youtu.be/_KFsggUGK08
Footprint of robots: http://youtu.be/9ZArK2Adb48
-coded by Srikanth.K.V.S and Aaron.T.Becker

Cite As

Srikanth Kandanuru Venkata Sudarshan (2024). waypointContolForPathPlanningTWMCS() (https://www.mathworks.com/matlabcentral/fileexchange/49863-waypointcontolforpathplanningtwmcs), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014b
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Version Published Release Notes
1.5.0.0

The code has been improved by making all waypoints move one at a time every iteration. The cost function used is a binary function and it can be switched. We have included a provision of recording the simulation.
The code was updated, Video links to the simulation of single-robot, multi-robot and foot prints of robots are added. Watch and enjoy.
1.4.0.0

Added a Profile Picture!!!
1.3.0.0

Updated the summary and vectorized the code so that the simulation speeds-up.
1.2.0.0

Updated the previous code
1.1.0.0

An update of the algorithm and the way the code is presented.
1.0.0.0