Ph.D. Proposal: Venkata Ramana Makkapati

Fri Nov 15 2019 01:30 PM to 02:30 PM
W200, Weber Space Science and Technology Building
“Pursuit-Evasion with Multiple Agents and Uncertainties”

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Ph.D. Proposal


Venkata Ramana Makkapati

(Advisor: Prof. Panagiotis Tsiotras)


“Pursuit-Evasion with Multiple Agents and Uncertainties”


Friday, November 15 at 1:30 p.m.
W200, Weber Space Science and Technology Building


According to the reports, the global UAV market generated $26 billion in 2018, and is expected to grow at a compound annual growth rate of 8.45% during the period 2019-29. Over the past decade, there have been constant efforts to induct unmanned aerial vehicles (UAVs) into military engagements, disaster management, weather monitoring, and package delivery, among various other applications. With UAVs starting to come out of controlled environments into real-world scenarios, uncertainties which can be either exogenous or endogenous play an important role in the planning and decision-making aspects of deploying UAVs. Simultaneously, while the demand for UAVs is steadily increasing, major governments are working on their regulations, and there is an urgency to design surveillance and security systems that can efficiently regulate the traffic and usage of these UAVs, especially in secured airspaces.  With this motivation, the thesis primarily focuses on airspace security, and safe planning under uncertainties. To this end, we employ the pursuit-evasion framework, rooted in the differential game theory, that mathematically formalizes and provides solutions for target acquisition, collision avoidance, rendezvous, apart from its insights into zoological phenomena.


In this thesis proposal, we first summarize our work on solutions developed for airspace security that employ multiple agents to capture multiple targets in an efficient manner. Next, we formalize planning under parametric uncertainties and to this end, sensitivity functions and costates based techniques are introduced. Preliminary results suggest that a trade-off between optimality and intensity in the variations under parametric uncertainties can be obtained.  Utilizing those results, we propose to address the problem of safe path planning under uncertainties in dynamic obstacles, and its game-theoretic counterpart which is useful in a fog of war situation. Finally, we consider stochastic disturbances, and propose to analyze the pursuit-evasion problem under stochastic flow fields using forward reachability analysis, and covariance steering.



  • Prof. Panagiotis Tsiotras – School of Aerospace Engineering, Georgia Institute of Technology
  • Prof. Seth Hutchinson – School of Interactive Computing, Georgia Institute of Technology
  • Prof. Kyriakos Vamvoudakis – School of Aerospace Engineering, Georgia Institute of Technology


W200, Weber Space Science and Technology Building