Falling Object Simulator – Simulation & Concurrency



As part of my MSC Computer Science degree, the Simulation & Concurrency module was probably the most intense module on the course, tasking us to produce a physics engine from scratch with robust network and multi-threading integration in order to implement a simulation of balls falling into a box, with removable trays and also a cloth simulated net.

Having done only a little previous physics programming for ‘The Column’, I set about researching the topic since implementing a solid and robust physics engine is no trivial task, even without a networking element. Although I found several good sources, for specific elements, Ian Millington’s ‘Game Physics Engine Development’ was an excellent book that covered many aspects of getting a basic physics engine up and running. I promptly devoured about a third of the book during this project though it lacks any real depth on collision detection and doesn’t real cover cloth simulation as I recall.

In the end I received 87% for the ACW which I’m pleased with. With more time I would have implemented rigid body motion but this second semester of the MSc has been pretty insane in terms of work load, mainly due to the fact that the UK carries out MSc degrees in a single year, rather then 2 like everywhere else in the world! Additionally, the University of Hull’s MSc degree is extremely practical, which although I find preferable to more theoretical based degrees (how better to learn then via implementation?) does result in a heavy work load. The good side is that if you put the work in, your get an extensive portfolio at the end of the degree.

Project Description:

The result of the project was a multi-threaded interactive falling object simulator developed from scratch using C++ and DirectX 11. The physics engine is a mass aggregate system using particles i.e. no rigid body motion. It features simple sphere and plane based collision detection and interpenetration resolution.

Each tray features different friction and elasticity attributes as per the specification.

An advanced feature is the cloth simulation for the net made using a lattice of spring constraints (Hook’s law) with four anchored corners.

Net collision detection is made using small spheres mapped to the vertices of the net, this however means I had to make the springs quite rigid to stop balls from forcing their way in-between the vertices hence the cloth is not very fluid or fluttery.

Without rigid body dynamics to get the cube rotations I used rod constraints connected to each vertex of the cube. This is a simple way to get rotations using just particles.

Rendering and physics integration are performed on separate threads, with an additional 3 threads for handling network. Rendering frame rate is hence independent from the simulation and both can be changed to run at a specific target rate.

Not shown in the video, but being a significant part of the project is the peer-to-peer network aspect. The program can be run on 2 peers, each peer will communicate and synchronise the simulation using linear interpolation of the scenes physics data. Each peer can be interacted with i.e. camera can be moved independently (think multiplayer) and commands such as open/close tray and spawn ball is communicated across the network to each peer. Network coding was done using Winsock. UDP broadcasting was used purely for peer detection and TCP for data transmission. Packet loss and latency resilience was also implemented.