scholarly journals Implementation of a novel reactive navigation algorithm

2021 ◽  
Author(s):  
Vijay Somers

In this project a reactive navigation algorithm is applied to a non-holonomic differential drive robot. The algorithm uses a stochastic process to navigate a robot through terrain while lacking a priori information. A graph is made from a random array of points that is used to connect the current location of the robot to its destination. Dijkstra's algorithm is used to select the shortest route that leads to the destination. The robot attempts to traverse this route until it detects that it is being blocked by an obstacle. The graph is then recreated with different random points, an a new route is calculated. This procedure is repeated until the robot arrives at its destination. This is tested by making a simulated robot with perfect localization travel through two kinds of environments. Processing speed is maintained by hashing location information according to its coordinates.

2021 ◽  
Author(s):  
Vijay Somers

In this project a reactive navigation algorithm is applied to a non-holonomic differential drive robot. The algorithm uses a stochastic process to navigate a robot through terrain while lacking a priori information. A graph is made from a random array of points that is used to connect the current location of the robot to its destination. Dijkstra's algorithm is used to select the shortest route that leads to the destination. The robot attempts to traverse this route until it detects that it is being blocked by an obstacle. The graph is then recreated with different random points, an a new route is calculated. This procedure is repeated until the robot arrives at its destination. This is tested by making a simulated robot with perfect localization travel through two kinds of environments. Processing speed is maintained by hashing location information according to its coordinates.


2017 ◽  
Vol 14 (3) ◽  
pp. 365-377
Author(s):  
Evgenii Semenishchev ◽  
Igor Shraifel ◽  
Ilya Svirin

The paper presents a method for smoothing signals represented by a single realization of a finite-length random process, under conditions of a limited amount of a priori information about the signal function and statistical characteristics the noise component. The recommendations on the use of parameters affecting the processing speed and the efficiency of smoothing are given. Two solutions are presented to obtain the result of smoothing the signals. The efficiency results are shown for the processing of digital signals. Examples of comparison of simple methods and suggested ones are given.


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