Transcript PPT
Fusion of Evolutionary
Algorithms and Multi-Neuron
Heuristic Search for Robotic
Path Planning
Rahul Kala,
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
http://students.iiitm.ac.in/~ipg_200545/
[email protected],
[email protected]
Publication of paper:R. Kala, A. Shukla, R. Tiwari (2009) Fusion of Evolutionary Algorithms and MultiNeuron Heuristic Search for Robotic Path Planning, Proceedings of the 2009 IEEE World Congress on
Nature & Biologically Inspired Computing, Coimbatote, India, pp. 684 – 689.
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
The Problem
Inputs
◦ Robotic Map
◦ Location of Obstacles
◦ Static and Dynamic
Output
◦ Path P such that no collision occurs
Constraints
◦ Time Constraints
◦ Dimensionality of Map
◦ Static and Dynamic Environment
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
MNHS Algorithm
In all we take α neurons.
We have a list of heuristic costs each corresponding to
node seen but waiting to be processed.
We divide the cost range into α ranges equally among
them. Each of these neurons is given a particular range.
Each neuron selects the minimum most element of the
cost range allotted to it and starts searching.
At one step of each neuron processes its element by
searching and expanding the element.
This process is repeated.
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Path Generation
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Evolutionary Algorithm
Individual
Representation
Conversion to
graph
Evolutionary
Operators
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Individual Representation
Set of points P <P0, P1,
P2, P3, …. Pn, Pn+1>.
P0 is the source and
Pn+1 is the goal.
X axis is the straight
line joining the source
and the goal. The Y
axis is perpendicular
All points
represented by the
individual are sorted
by their x axis values.
Y
Source
P0
(0,0)
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
α
P1
(x,y)
P2
P3
P4
Goal
X
X’
P5
(m’,n’)
MTech Thesis Fourth
Evaluation
Genetic Operators
Crossover
Mutation
Rank based fitness scaling
Stochastic uniform selection
Diversity Preservation Selection
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Fusion
MNHS reduces number of points for EA
EA gives iterative approach
Select Prospective Best points by EA and
Build actual solution by MNHS
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Results
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Publications
Kala, Rahul, Shukla, Anupam, & Tiwari, Ritu (2010) Robotic Path Planning using Evolutionary
Momentum based Exploration, Journal of Experimental and Theoretical Artificial Intelligence,
Taylor and Francis Publishers (Impact Factor: 0.341)
Kala, Rahul, Shukla, Anupam, & Tiwari, Ritu (2010) Fusion of probabilistic A* algorithm and
fuzzy inference system for robotic path planning, Artificial Intelligence Review, Springer
Publishers, Vol. 33, No. 4, pp 275-306 (Impact Factor: 0.119)
Kala, Rahul, Shukla, Anupam, & Tiwari, Ritu (2009) Fusion of Evolutionary Algorithms and
Multi-Neuron Heuristic Search for Robotic Path Planning, Proceedings of the IEEE 2009
World Congress on Nature & Biologically Inspired Computing, NABIC '09, pp 684 - 689,
Coimbatore, India
Kala, Rahul, Shukla, Anupam, & Tiwari, Ritu (2009), Robotic Path Planning using Multi
Neuron Heuristic Search, Proceedings of the ACM 2009 International Conference on Computer
Sciences and Convergence Information Technology, ICCIT 2009, pp 1318-1323, Seoul, Korea
Kala, Rahul, Shukla, Anupam, Tiwari, Ritu, Roongta, Sourabh & Janghel, RR (2009) Mobile
Robot Navigation Control in Moving Obstacle Environment using Genetic Algorithm,
Artificial Neural Networks and A* Algorithm, Proceedings of the IEEE World Congress on
Computer Science and Information Engineering, CSIE 2009, pp 705-713, Los Angeles/Anaheim,
USA
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation
Thank You
Soft Computing and Expert System Laboratory
Indian Institute of Information Technology and Management Gwalior
MTech Thesis Fourth
Evaluation