In my research, I aim to achieve scalable, cooperative coordination of robots by studying their interactions from a game-theoretic standpoint. My research interests include Multi-Robot Systems, Game Theory and Multi-Agent Reinforcement Learning. Additionally, I am also serving as the Vice-Chair of the IEEE Indiana University student branch.


I am actively looking for research positions, broadly in multi-robot systems, UAV control, and multi-agent reinforcement learning.


  • (2022 May) I presented at the Workshop on Intelligent Aerial Robotics , International Conference on Robotics and Automation – 2022, Philadelphia.
  • (2022 March) A new paper accepted to IEEE Robotics and Automation Letters (RA-L): “CoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage” [Paper].
  • (2022 February) Mavswarm‘s new features support adding heterogeneous quadrotor models and receding horizon planning (RHP) out-of-the-box. Check it out: github.com/malintha/multi_uav_simulator.

Recent Work

CoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage.

CoCo Games is a multi-robot coverage scheme focused on providing communication-aware coverage for a large Region of Interest (ROI). Specifically, CoCo Games can be used to coordinate UAV swarms to establish ad-hoc mobile wireless networks for stationary and moving ground robot teams in real-time. Project website: https://malintha.github.io/coco/.

Online Flocking Control of UAVs with Mean-Field Approximation

In this work we cast the aerial swarm flocking as a probabilistic inference and utilize mean-field approximation to infer the control actions for the robots in real time. This allows achieving dynamically feasible real-time flocking control with convergence guarantees borrowed from graphical games.

Flocking of Multi Aerial Vehicles Generation of flocking behavior for UAV swarms in confined areas.


MavSwarm A robust and light weight multi UAV dynamics simulator based on Robot Operating System (ROS). Find the code at https://github.com/Malintha/multi_uav_simulator


Formation Control and Navigation of a Quadrotor Swarm A swarm of Crazyflie nano drones are controlled by using rigid body dynamics. Published at International Conference on Unmanned Aircraft Systems (2019).


Aggressive and Precise Maneuvering of a Crazyflie Nano Drone This work includes generating smooth, piecewise trajectories with quadratic programming.