Leges Motus

Image showing red and blue players firing lasers at each other in a 2D zero-gravity arena.


A multiplayer game of laser tag in zero-gravity, 2D environments. By jumping off the walls and using your favorite laser weapon, defeat the opposing team to capture their base!

Research Topics

Game Engines | Pathfinding | Fuzzy Logic | Utility


Vicki Pfau | Andrew Ayer | Danny Schneider


The Leges Motus project began as a simple multiplayer game of laser tag, set in 2D zero-gravity arenas, written in a custom engine in C++ with SDL and OpenGL. The game combines simple, fast-paced gameplay with team strategy and tactics in several game modes, with three different weapons available to enable several play-styles. Later, we researched and implemented AI features in the game.

The AI for Leges Motus is primarily a fuzzy logic system (Klir and Yuan 1996), similar to a utility-theory-based AI (Russell and Norvig 2016). The agents calculate their strategy based on a hand-authored combination of multiple perceived game state features. The AI also requires a unique pathfinding solution. Because of the zero-gravity environment, agents cannot change direction in mid-air. Therefore, we use raycast sweeps to calculate a connected graph of possible jump points on each wall, enabling us to perform an A* pathfinding search (Hart et. al. 1968) on the resulting graph.

Leges Motus is available for Mac, Linux, and Windows as a binary for the stable version, 0.4, and the code is open source for both the stable version and the unstable, refactored version 0.5, which is missing some UI and game mode features. Development is currently on indefinite hiatus.


Playable, Dormant


Hart, P. E., N. J. Nilsson, and B. Raphael. 1968. “A Formal Basis for the Heuristic Determination of Minimum Cost Paths.” IEEE Transactions on Systems Science and Cybernetics 4 (2): 100–107. https://doi.org/10.1109/TSSC.1968.300136.
Klir, George J., and Bo Yuan. 1996. Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A. Zadeh. World Scientific Publishing Co., Inc.
Russell, Stuart J., and Peter Norvig. 2016. Artificial Intelligence: A Modern Approach. Malaysia; Pearson Education Limited,.


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