Distance Computation between Convex Objects using Axis-Aligned Bounding-Box in Virtual Environment Application

Performing collision detection between convex objects in virtual environment simulation is one of vital problems in computer visualization research area. Given a set of two or more colliding objects, in order to determine the exact point of contact between object we need to undergo various high computation algorithm. In this paper, we describes our current work of determining the precise contact by measuring the distance between near colliding objects in order to maintain the accuracy and improve the speed of collision detection algorithm. Common method determine the distance by checking for vertices and edges point between objects in brute force condition. Compared to our method, by given set of objects in virtual environment world, we find the closest point between near colliding objects and bound the potential colliding area with an Axis-Aligned Bounding-Box. Then, we approximate the distance by measuring the distance of the box itself and hence recognize potential colliding area faster than the common method. Our method proven to most effective and efficient for narrow phase collision detection by removing unnecessary testing and reduced computational cost

Distance Approximation using Pivot Point in Narrow Phase Collision Detection

Discrete and Continuous Collision Detection is two common fields in Collision Detection research area where it helps to determine time and point of contact when two object intersect. Each technique increase speed and accuracy of the simulation itself but depending on application, we need to have specific solution of collision detection technique. Most computer games and simulation maintain speed as the main important elements while others such as medical and mechanical simulation needs to have a very high precision collision detection technique. Thus, an algorithm for the optimal distance computation algorithm for continuous collision detection is shown in this paper. The basic idea is to use an AABB for both object triangles and creating a moveable origin point called Dynamic Origin Point (DyOP). DyOP created by using minimum and maximum point of both AABBs where it dynamically changes whenever the object move. This is a novel algorithm that works better than the previously known Gilbert Keerthi-Johnson algorithm and Lin-Canny algorithm where it helps to reduce the complicated test and implementation. We have shown that our technique is performed faster than the previous algorithms by increasing speed and nearly approximate the good distance between two nearly intersected triangles

Measuring Distance between Nearly Intersected Objects in Narrow Phase Collision Detection

Calculating the distance between two or more object primitives (or triangles) in virtual environment application before collision occurs is important elements in narrow phase collision detection system. Given pairs of nearly colliding objects, their triangles must be checked one by one until the most shortest distance is founded and thus the computation cost for checking collision reduced by checking the nearest triangles that possible to collide. Hence, in this research, we used Heron’s formula for calculating the distance between objects that nearly collide and compared it using vector-based calculation. We have found that the formula increased the speed of distance computation slightly faster compared to the vector-based calculation for single triangle checking with minimum memory requirements. In this paper, we explained the procedures of using Heron’s Formula and vector-based techniques for computing distance and the experimental results between those two techniques. It is believed that it could help to speed up the process of determine the precise contact between colliding objects while maintaining the accuracy of the collision checkin