The topic is Vision based obstacle avoidance in Mobile Robot using Swarm optimization technique.
If the technical team suggests any other title relevant to this, we can change the title as they have better knowledge than me.
Target Journal: SCI Elsevier Engineering Application of Artificial Intelligence.
Topic: Vision based obstacle avoidance in Mobile Robot using Swarm optimization technique.
Mode of Code Implementation: Python
Requirement:
Code and Paper Writing for SCI level journal paper (Elsevier Engineering Application of Artificial Intelligence)
Plot required: There has to be 4 method implemented:
1. MLP (Multi-Layer Perceptron) with Back Propagation algorithm
2. MLP with PSO (Particle Swarm Optimization) algorithm
3. Functional Link Artificial Neural Network(FLANN) with Least Mean Square(LMS) algorithm
4. FLANN with PSO algorithm
From each of the method, we want 2 output plot each
1. Mean Square Error (MSE) in db on y axis and Epoch on x axis
2. Deviation percent (between actual data and predicted data) on y axis and actual data(output) on x axis
You can take the output plot reference from page 8,9 in the attached paper name, "ann and pso"
The output of dataset is servo motor angle so we want to show at which angle the vehicle will turn to avoid obstacle.
Take reference from ann obstacle avoidance dataset paper
Mention about how data set is taken by taking reference from that paper
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