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Egerstedt, Magnus B.

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Now showing 1 - 9 of 9
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    Constructing and Implementing Motion Programs for Robotic Marionettes
    (Georgia Institute of Technology, 2011-04) Martin, Patrick ; Johnson, Elliot ; Murphey, Todd D. ; Egerstedt, Magnus B.
    This technical note investigates how to produce control programs for complex systems in a systematic manner. In particular, we present an abstraction-based approach to the specification and optimization of motion programs for controlling robot marionettes. The resulting programs are based on the concatenation of motion primitives and are further improved upon using recent results in optimal switch-time control. Simulations as well as experimental results illustrate the operation of the proposed method.
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    Autonomous Driving in Urban Environments: Approaches, Lessons, and Challenges
    (Georgia Institute of Technology, 2010) Campbell, M. ; Egerstedt, Magnus B. ; How, J. P. ; Murray, R. M.
    The development of autonomous vehicles for urban driving has seen rapid progress in the past 30 years. This paper provides a summary of the current state of the art in autonomous driving in urban environments, based primarily on the experiences of the authors in the 2007 DARPA Urban Challenge (DUC). The paper briefly summarizes the approaches that different teams used in the DUC, with the goal of describing some of the challenges that the teams faced in driving in urban environments. The paper also highlights the long-term research challenges that must be overcome in order to enable autonomous driving and points to opportunities for new technologies to be applied in improving vehicle safety, exploiting intelligent road infrastructure and enabling robotic vehicles operating in human environments.
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    Automatic Formation Deployment of Decentralized Heterogeneous Multiple-Robot Networks with Limited Sensing Capabilities
    (Georgia Institute of Technology, 2009-05) Smith, Brian Stephen ; Wang, Jiuguang ; Howard, Ayanna M. ; Egerstedt, Magnus B.
    Heterogeneous multi-robot networks require novel tools for applications that require achieving and maintaining formations. This is the case for distributing sensing devices with heterogeneous mobile sensor networks. Here, we consider a heterogeneous multi-robot network of mobile robots. The robots have a limited range in which they can estimate the relative position of other network members. The network is also heterogeneous in that only a subset of robots have localization ability. We develop a method for automatically configuring the heterogeneous network to deploy a desired formation at a desired location. This method guarantees that network members without localization are deployed to the correct location in the environment for the sensor placement
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    Automatic Generation of Persistent Formations for Multi-Agent Networks Under Range Constraints
    (Georgia Institute of Technology, 2009-04) Smith, Brian Stephen ; Howard, Ayanna M. ; Egerstedt, Magnus B.
    In this paper we present a collection of graphbased methods for determining if a team of mobile robots, subjected to sensor and communication range constraints, can persistently achieve a specified formation. What we mean by this is that the formation, once achieved, will be preserved by the direct maintenance of the smallest subset of all possible pairwise interagent distances. In this context, formations are defined by sets of points separated by distances corresponding to desired inter-agent distances. Further, we provide graph operations to describe agent interactions that implement a given formation, as well as an algorithm that, given a persistent formation, automatically generates a sequence of such operations. Experimental results are presented that illustrate the operation of the proposed methods on real robot platforms.
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    Multi-Robot Deployment and Coordination with Embedded Graph Grammars
    (Georgia Institute of Technology, 2009-01) Smith, Brian Stephen ; Howard, Ayanna M. ; McNew, John-Michael ; Egerstedt, Magnus B.
    This paper presents a framework for going from specifications to implementations of decentralized control strategies for multi-robot systems. In particular, we show how the use of Embedded Graph Grammars (EGGs) provides a tool for characterizing local interaction and control laws. This paper highlights some key implementation aspects of the EGG formalism, and develops and discusses experimental results for a hexapod-based multi-robot system, as well as a multi-robot system of wheeled robots.
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    Multi-robot deployment and coordination with Embedded Graph Grammars
    (Georgia Institute of Technology, 2009-01) Smith, Brian Stephen ; Howard, Ayanna M. ; McNew, John-Michael ; Wang, Jiuguang ; Egerstedt, Magnus B.
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    Automatic Generation of Persistent Formations for Multi-agent Networks under Range Constraints
    (Georgia Institute of Technology, 2007-10) Smith, Brian Stephen ; Howard, Ayanna M. ; Egerstedt, Magnus B.
    We present graph-based methods for determining if a mobile robot network with a defined sensor and communication range can persistently achieve a specified formation, which implies that the formation, once achieved, will be preserved by the direct maintenance of a subset of inter-agent distances. Here, formations are defined by a set of points whose inter-point distances correspond to desired inter-agent distances. Further, we provide graph operations to describe agent interactions that implement a given formation, as well as an algorithm that, given a persistent formation, automatically generates a sequence of such operations.
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    Optimal Trajectory Planning and Smoothing Splines
    (Georgia Institute of Technology, 2001-07) Egerstedt, Magnus B. ; Martin, Clyde F.
    In this paper, some of the relationships between optimal control and trajectory planning are examined. When planning trajectories for linear control systems, a demand that arises naturally in air traffic control or noise contaminated data interpolation is that the curve passes close to given points, or through intervals, at given times. In this paper, we produce these curves by solving an optimal control problem for linear control systems, while driving the output of the system close to the waypoints. We furthermore show how this optimal control problem reduces to a finite, quadratic programming problem, and we thus provide a constructive, yet theoretically sound framework for producing a rich set of curves called smoothing splines.
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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.