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Egerstedt, Magnus B.

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Now showing 1 - 9 of 9
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    Optimization of Multi-Agent Motion Programs with Applications to Robotic Marionettes
    (Georgia Institute of Technology, 2009-04) Martin, Patrick ; Egerstedt, Magnus B.
    In this paper, we consider the problem of generating optimized, executable control code from high-level, symbolic specifications. In particular, we construct symbolic control programs using strings from a motion description language with a nominal set of motion parameters, such as temporal duration and energy, embedded within each mode. These parameters are then optimized over, using tools from optimal switch-time control and decentralized optimization of separable network problems. The resulting methodology is applied to the problem of controlling robotic marionettes, and we demonstrate its operation on an example scenario involving symbolic puppet plays defined for multiple puppets.
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    An Information Space View of "Time": From Clocks to Open-Loop Control
    (Georgia Institute of Technology, 2009) LaValle, Steven M. ; Egerstedt, Magnus B.
    This paper addresses the peculiar treatment that time receives when studying control systems. For example, why is the ability to perfectly observe time assumed implicitly in virtually all control formulations? What happens if this implicit assumption is violated? It turns out that some basic control results fall apart when time cannot be perfectly measured. To make this explicit, we introduce information space concepts that permit imperfect time information to be considered in the same way as imperfect state information. We then argue that classical open-loop control should be reconsidered as perfect time-feedback control. Following this, we introduce a notion of strongly open-loop control, which does not require perfect time observations. We provide some examples of these concepts and argue that many fascinating directions for future controls research emerge.
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    Solving Coverage Problems with Embedded Graph Grammars
    (Georgia Institute of Technology, 2007-04) McNew, John-Michael ; Klavins, Eric ; Egerstedt, Magnus B.
    We show how Embedded Graph Grammars (EGGs) are used to specify local interaction rules between mobile robots in a natural manner. This formalism allows us to treat local network topologies, geometric transition conditions, and individual robot dynamics and control modes in a unified framework. An example EGG is demonstrated that achieves sensor coverage in a provably stable and correct manner. The algorithm results in a global network with a lattice-like triangulation.
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    Learning Multi-Modal Control Programs
    (Georgia Institute of Technology, 2005-03) Mehta, Tejas R. ; Egerstedt, Magnus B.
    Multi-modal control is a commonly used design tool for breaking up complex control tasks into sequences of simpler tasks. In this paper, we show that by viewing the control space as a set of such tokenized instructions rather than as real-valued signals, reinforcement learning becomes applicable to continuous-time control systems. In fact, we show how a combination of state-space exploration and multi-modal control converts the original system into a finite state machine, on which Q-learning can be utilized.
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    From Empirical Data to Multi-Modal Control Procedures
    (Georgia Institute of Technology, 2005) Delmotte, Florent ; Egerstedt, Magnus B.
    In this paper we study the problem of generating control programs, i.e. strings of symbolic descriptions of control-interrupt pairs (or modes) from input-output data. In particular, we take the point of view that such control programs have an information theoretic content and thus that they can be more or less effectively coded. As a result, we focus our attention on the problem of producing low-complexity programs by recovering the strings that contain the smallest number of distinct modes. An example is provided where the data is obtained by tracking ten roaming ants in a tank.
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    Control of Autonomous Mobile Robots
    (Georgia Institute of Technology, 2005) Egerstedt, Magnus B.
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    Motion Description Languages for Multi-Modal Control in Robotics
    (Georgia Institute of Technology, 2002-12) Egerstedt, Magnus B.
    In this paper we outline how motion description languages provide useful tools when designing multi-modal control laws in robotics. Of particular importance is the introduction of the description length as a measure of how complicated a given control procedure is. This measure corresponds to the number of bits needed for coding the input string. Description length arguments can furthermore be invoked for selecting sensors and actuators in a given robotics application, thus providing a unified framework in which a number of major areas of robotics research can coexist.
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    Behavior Based Robotics Using Hybrid Automata
    (Georgia Institute of Technology, 2000-03) Egerstedt, Magnus B.
    In this article, we show how a behavior based control system for autonomous robots can be modeled as a hybrid automaton, where each node corresponds to a distinct robot behavior. This type of construction gives rise to chattering executions, but we show how regularized automata suggest a solution to this problem. We also discuss some design and implementation issues.
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    Path Planning and Flight Controller Scheduling for an Autonomous Helicopter
    (Georgia Institute of Technology, 1999-03) Egerstedt, Magnus B. ; Koo, T. J. ; Hoffmann, F. ; Sastry, S.
    In this article we investigate how to generate flight trajectories for an autonomous helicopter. The planning strategy that we propose reflects the controller architecture. It is reasonable to identify different flight modes such as take-off, cruise, turn and landing, which can be used to compose an entire flight path. Given a set of nominal waypoints we generate trajectories that interpolate close to these points. This path generation is done for two different cases, corresponding to two controllers that either govern position or velocity of the helicopter. Based on a given cost functional, the planner selects the optimal one among these multiple paths. This approach thus provide a systematic way for generating not only the flight path, but also a suitable switching strategy, i.e. when to switch between the different controllers.