Path Planning and Control of various moving robots using Artificial Intelligence techniques in unknown cluttered environment

Rawat, Himanshu (2018) Path Planning and Control of various moving robots using Artificial Intelligence techniques in unknown cluttered environment. MTech thesis.

[img]PDF (10/02/2021)
Restricted to Repository staff only

2148Kb

Abstract

A lot of research has been done in the field of path planning of wheeled as well as humanoid robots in the last few decades. The main motive of the research being conducted in the field of humanoid robotics is to imitate human like motions so that they can replace humans
in hazardous situations and can work robustly, increasing production and helping humans in day today tasks. In this research, path planning of a wheeled mobile robot is done using Mamdani Fuzzy technique. The results obtained from experimental and simulation trials are
compared and found be in agreement. In the next phase of the research, focus concentrated on achieving path planning in humanoid NAO. Path planning of humanoid NAO is attempted using a classical technique i.e. Artificial Potential Field Method and an artificial intelligence
technique i.e. Cuckoo Search algorithm. In the final phase of this research, the navigational problem of a humanoid ROBONOVA is solved using a hybrid firefly neuro-fuzzy based algorithm. A comparative study is done between the experimental and simulation results
obtained from both the techniques. Simulations for humanoid NAO are performed on V-REP software. Analysis of humanoid ROBONOVA is also done using a hybrid technique and results
were recorded and compared

Item Type:Thesis (MTech)
Uncontrolled Keywords:Cuckoo search; Humanoid NAO; hybrid firefly; Mamdani fuzzy; Wheeled robot; Path planning; potential field; V-REP
Subjects:Engineering and Technology > Mechanical Engineering > Robotics
Engineering and Technology > Mechanical Engineering > Machine Design
Divisions: Engineering and Technology > Department of Mechanical Engineering
ID Code:9741
Deposited By:IR Staff BPCL
Deposited On:05 Feb 2019 16:02
Last Modified:05 Feb 2019 16:02
Supervisor(s):Parhi, Dayal R

Repository Staff Only: item control page