Mechanics Analyses | Drone Interceptors | Log 1
Project Overview
Published: Jan 4th, 2023
A group project undertaken at University as part of our Research and Development module.
The Brief
"Lots of interception strategies have been proposed from one-on-one to launch everything. The best way to evaluate the most effective interception strategy is for people to play a simulation or game in which ‘offensive’ player(s) try ideas to get through and ‘defensive’ player(s) try to intercept them. A simulation/game could allow players to customise their drones with different capabilities. However, a player’s resources are limited so larger/more complex drones means fewer drones. What is the optimal balance? Devise a game/simulator which demonstrates how a swarm of drones can be intercepted by another swarm of drones."
Concept
As a group we decided on the following idea: a two-player strategy game where players outfit drones to attack or defend against each others drone swarms. Both players are given limited resources to outfit their arsenal of drones. The drones are mostly self-autonomous, but each player is given some high-level of control to issue basic commands.
My Contribution/Role
My responsibility for this project was to develop the drone assembly system.
Key Objectives
- Stream in real-world locations to test drones more effectively
- Build a loadout system that enables drones to be outfitted with components
- Be able to issue commands to drones to control their behaviour
- Develop a replayability system to provide post-match analytics
- Utilise both PvE and PvP game environments for testing drones against
Game Mechanics
- Drone Classes
- Drone Swarm Movement - Flocking Behaviour
- Drone Swarm Combat - Decision-making Techniques To Control Ai Behaviour
- Drone Customisation
- Resource Budgeting
- Strategic Drone/Defense Placement - Tactical Map
- Replayability System
- PvE and PvP Game Environments
- Mission System
- Dynamic Weather - Strong Winds, Heavy Fog