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Jagannath Aghav

Publications and source records attributed to Jagannath Aghav.

2 recordsLinked to original sources

Automated Training and Maintenance through Kinect

In this paper, we have worked on reducing burden on mechanic involving complex automobile maintenance activities that are performed in centralised workshops. We have presented a system prototype that combines Augmented Reality with Kinect. With the use of Kinect, very high quality sensors are available at considerably low costs, thus reducing overall expenditure for system design. The system can be operated either in Speech mode or in Gesture mode. The system can be controlled by various audio commands if user opts for Speech mode. The same controlling can also be done by using a set of Gestures in Gesture mode. Gesture recognition is the task performed by Kinect system. This system, bundled with RGB and Depth camera, processes the skeletal data by keeping track of 20 different body joints. Recognizing Gestures is done by verifying user movements and checking them against predefined condition. Augmented Reality module captures real-time image data streams from high resolution camera. This module then generates 3D model that is superimposed on real time data.

cs.CV

Design and Validation of Safety Cruise Control System for Automobiles

In light of the recent humongous growth of the human population worldwide, there has also been a voluminous and uncontrolled growth of vehicles, which has consequently increased the number of road accidents to a large extent. In lieu of a solution to the above mentioned issue, our system is an attempt to mitigate the same using synchronous programming language. The aim is to develop a safety crash warning system that will address the rear end crashes and also take over the controlling of the vehicle when the threat is at a very high level. Adapting according to the environmental conditions is also a prominent feature of the system. Safety System provides warnings to drivers to assist in avoiding rear-end crashes with other vehicles. Initially the system provides a low level alarm and as the severity of the threat increases the level of warnings or alerts also rises. At the highest level of threat, the system enters in a Cruise Control Mode, wherein the system controls the speed of the vehicle by controlling the engine throttle and if permitted, the brake system of the vehicle. We focus on this crash area as it has a very high percentage of the crash-related fatalities. To prove the feasibility, robustness and reliability of the system, we have also proved some of the properties of the system using temporal logic along with a reference implementation in ESTEREL. To bolster the same, we have formally verified various properties of the system along with their proofs.

cs.SE