An Unmanned Aerial Vehicle as Human-Assistant Robotics System

According to the American Heritage Dictionary [1],Robotics is the science or study of the technology associated with the design, fabrication, theory, and application of Robots. The term Hoverbot is also often used to refer to sophisticated mechanical devices that are remotely controlled by human beings even though these devices are not autonomous. This paper describes a remotely controlled hoverbot by installing a transmitter and receiver on both sides that is the control computer (PC) and the hoverbot respectively. Data is transmitted as signal or instruction via a infrastructure network which is converted into a command for the hoverbot that operates at a remote site.

An Artificial Immune System Model for Multi-Agents Resource Sharing in Distributed Environments

Natural Immune system plays a vital role in the survival of the all living being. It provides a mechanism to defend itself from external predates making it consistent systems, capable of adapting itself for survival incase of changes. The human immune system has motivated scientists and engineers for finding powerful information processing algorithms that has solved complex engineering tasks. This paper explores one of the various possibilities for solving problem in a Multiagent scenario wherein multiple robots are deployed to achieve a goal collectively. The final goal is dependent on the performance of individual robot and its survival without having to lose its energy beyond a predetermined threshold value by deploying an evolutionary computational technique otherwise called the artificial immune system that imitates the biological immune system.

Land-cover Classification and Mapping for Eastern Himalayan State Sikkim

Area of classifying satellite imagery has become a challenging task in current era where there is tremendous growth in settlement i.e. construction of buildings, roads, bridges, dam etc. This paper suggests an improvised k-means and Artificial Neural Network (ANN) classifier for land-cover mapping of Eastern Himalayan state Sikkim. The improvised k-means algorithm shows satisfactory results compared to existing methods that includes k-Nearest Neighbor and maximum likelihood classifier. The strength of the Artificial Neural Network (ANN) classifier lies in the fact that they are fast and have good recognition rate and it's capability of self-learning compared to other classification algorithms has made it widely accepted. Classifier based on ANN shows satisfactory and accurate result in comparison with the classical method.