Use of non-immersive virtual reality in mechanical engineering laboratory
RMahalinga Iyer, C Frieiberg
- Year
- 2005
- Citations
- 4
Abstract
Virtual Reality (VR) differs from computer animation in two distinct ways. Firstly, VR allows users to randomly interact with the computer generated world. Secondly, the objects within this synthetic environment are three dimensional. There are three functional groups within Virtual Reality. They are: immersive, non-immersive and augmented or hybrid systems. In nonimmersive VR, the user interacts with the synthetic environment without the assistance of specialized environment or equipment such as the CAVE or gloves etc. The manipulation of the environment is done by a mouse or a joy-stick. This paper is confined to non-immersive virtual reality systems. Traditional Mechanical Engineering laboratory experiments (or any other engineering laboratory experiments) are done within a limited time. In many cases, the students will not know how to operate a piece of equipment. The training required for such purpose is prohibitive both in time and finance, to any Engineering School. It would be extremely beneficial, if the students can prepare themselves, prior to attending the laboratory session, to have some prior knowledge on how to use the equipment and collect data. The Virtual Reality system, if implemented properly, will provide such an opportunity for the student to practice the laboratory exercises before commencing the physical experiment. This paper will review some of the existing systems; describe the use of a commercial VR system to train the students to program a Mitsubishi robot and the development of an in house system to enhance the experience in using a Hounsfield tensometer for testing the strength of materials. The paper will also discuss the preliminary evaluation of the usefulness of the VR-Robot system.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002