Reflection:Due to the Liv. Hackathon in week 4 that my team attended, class was rescheduled to Wednesday in week 5, and all of this week we dedicated it to project development and consultation classes so that we could get ahead with development progress on the game. In week 6, however, during the weekday classes we dedicated most of the classes to project development, except on Thursday when we were introduced to Group AI behaviors, though we only managed to cover BOIDS. In terms of BOIDS, we were introduced to the method with which BOIDS operated. BOIDS simulate the behavior of a flock of birds – avoiding each other while following each other and trying to stay together – controlling the whole flock using 3 simple vector behaviors in both 2D and 3D space. These behaviors are called Separation, Cohesion and Alignment. These are 3 simple vectors that help to realistically simulate the flocking behavior (Pemmaraju, V. P. V, 2013). From this point on in BOIDS, I’ll be referring to Pemmaraju, V. P. V’s article on BOIDS. Separation is exactly what it means – it’s the vector that handles the separation of the individual boid in the flock, where each boid will always try to keep a good amount of distance between other boids. To do this, the vector takes in the average positions of every boid in its radial range and points its resultant vector in the opposite direction with a similar magnitude. Cohesion is the vector behavior that causes the boids to essentially keep itself inside the average center of mass of the surrounding flock. With that said, Cohesion also takes in the average positions of the surrounding boids and points its vector in the direction of that average center of mass and steers the boid towards it. Alignment is similar to Cohesion except it tries to line itself up with nearby boids. This doesn’t need to take in an average position since Separation and Cohesion already do that, but it does need an average velocity in order to follow along the flock’s movement. The function will simply return this vector and steer the boid in the direction of the average velocity. Add all 3 of these vector forces into a steering behavior like Seek and the resulting movement will smoothly simulate the flock behavior. Studio Team:These two weeks, the studio team went out of the planning phase and began production on the game. We split the tasks evenly amongst ourselves. For the game designers, they we made to split the work amongst themselves, especially their GDD to see who would come up with a better use for the mechanics that we discussed in the previous weeks. We were slightly slowed down by the 2-day hackathon that we attended, which was okay since, as I mentioned in the reflection section, we dedicated all of the classes in week 5 to working on the game. However, it would have been better for us to not have attended since it wasn’t really much of a hackathon, more like a big idea pitch to the company holding it. As for us programmers, we were given tasks according to the task breakdown. I was given the friendly towers targeting system and bullet variants to work on so that the game designers could have a much easier time while working on the game. I did this by using enums and switch cases, allowing the designers to simply change the type of tower it was (Single shot, AOE, Freeze and Slow type) and the kind of damage it will do. We’re using trello and following Agile to develop and track our game’s progress. Reference(s):Pemmaraju, V. P. V. (2013, January 21). 3 Simple Rules of Flocking Behaviors: Alignment, Cohesion, and Separation. Retrieved December 20, 2019, from https://gamedevelopment.tutsplus.com/tutorials/3-simple-rules-of-flocking-behaviors-alignment-cohesion-and-separation--gamedev-3444.
0 Comments
Leave a Reply. |
Categories |