IMPLEMENTATION OF A MACHINE LEARNING ALGORITHM FOR TERRAIN

PREDICTION ON A HEXAPOD DEVOID OF VISION

Introduction

This project attempts to emulate on a six legged robot the human approach towards walking. Previous work in the field of

autonomous navigation has centered greatly on the use of vision; the algorithm employed by this project endeavors to

refine the process of walking by emulating podiatric feedback using basic physics and brain function using a machine

learning algorithm. Alternately, the algorithm also presents a novel approach towards autonomous navigation, with

potential applications in aiding the navigation of autonomous robots devoid of vision capabilities.

(a)The design of the hexapod in Autodesk® Inventor (b) The actual design of the hexapod (c) The GUI designed in Processing for controlling the hexapod

Overview of the Algorithm

The aforementioned ideas are implemented through the use of a novel approach towards terrain prediction and mapping.

Vision-enabling peripherals being absent, the geography of a terrain is represented by a graph of the same, as sensed by

auxiliary peripherals. This approach employs a machine learning algorithm trained with a set of uniform ‘template’ terrains in

controlled conditions. The algorithm approximates unencountered terrain as a weighted combination of the ideal templates.

This approach being very basic, it accommodates sufficient modularity regarding the complexity of the algorithm.

Innovation

The implementation of the algorithm presented certain difficulties, many of which were overcome by employing original

techniques. For instance, the segregation of the input data into linearly- operable training data sets was done by defining a

characteristic “flexible hexagon” for each terrain, and statistical techniques for manipulating hexagonal graphs were

developed. An inverse kinematics algorithm for data collection was also developed indigenously, as was a two-pronged

learning mechanism for the machine learning algorithm.

or inverse kinematics \

Diagrams describing the various parameters of inverse

kinematics

Progress

A prototype of the proposed design of the hexapod showcasing its motor function and weight balancing capabilities as well

as its proposed tripod gait has been successfully implemented. Also, the algorithm was tested using simulated inputs for

proof of concept.

Results

Applications We envisage the aforementioned research to find applications in hostile environments requiring autonomous robot navigation

and effective system control, with poor visibility.

It may prove indispensable for defense purposes and can serve military purposes as effective mine-sweepers, stealth

scouts (night & day) etc.

The said algorithm & its implementation can be an effective alternative navigation control mechanism for

future space rovers & extra-terrestrial planet explorers.

It can also be employed for deep-sea exploration purposes, being a scenario with low visibility.

The proposed algorithm is analogous to the role of podiatric sensory system in human navigation of terrain –

thus, it can help create an infallible navigation system in tandem with vision feedback.

The steps according to which the

tripod gait has been implemented