64 research outputs found

    Formalizing behavior-based planning for nonholonomic robots

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    In this paper we present a formalization of behavior-based planning for nonholonomic robotic systems. This work provides a framework that integrates features of reactive planning models with modern control-theory-based robotic approaches in the area of path-planning for nonholonomic robots. In particular, we introduce a motion description language, MDLe, that provides a formal basis for robot programming using behaviors, and at the same time permits incorporation of kinematic models of robots given in the form of differential equations. The structure of the language MDLe is such as to allow descriptions of triggers (generated by sensors) in the language. Feedback and feedforward control laws are selected and executed by the triggering events. We demonstrate the use of MDLe in the area of motion planning for nonholonomic robots. Such models impose limitations on stabilizability via smooth feedback, i.e. piecing together open loop and closed loop trajectories becomes essential in these circumstances, and MDLe enables one to describe such piecing together in a systematic manner. A reactive planner using the formalism of the paper is described. We demonstrate obstacle avoidance with limited range sensors as a test of this planner.

    Coordination of Multirobot Teams and Groups in Constrained Environments: Models, Abstractions, and Control Policies

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    Robots can augment and even replace humans in dangerous environments, such as search and rescue and reconnaissance missions, yet robots used in these situations are largely tele-operated. In most cases, the robots\u27 performance depends on the operator\u27s ability to control and coordinate the robots, resulting in increased response time and poor situational awareness, and hindering multirobot cooperation. Many factors impede extended autonomy in these situations, including the unique nature of individual tasks, the number of robots needed, the complexity of coordinating heterogeneous robot teams, and the need to operate safely. These factors can be partly addressed by having many inexpensive robots and by control policies that provide guarantees on convergence and safety. In this thesis, we address the problem of synthesizing control policies for navigating teams of robots in constrained environments while providing guarantees on convergence and safety. The approach is as follows. We first model the configuration space of the group (a space in which the robots cannot violate the constraints) as a set of polytopes. For a group with a common goal configuration, we reduce complexity by constructing a configuration space for an abstracted group state. We then construct a discrete representation of the configuration space, on which we search for a path to the goal. Based on this path, we synthesize feedback controllers, decentralized affine controllers for kinematic systems and nonlinear feedback controllers for dynamical systems, on the polytopes, sequentially composing controllers to drive the system to the goal. We demonstrate the use of this method in urban environments and on groups of dynamical systems such as quadrotors. We reduce the complexity of multirobot coordination by using an informed graph search to simultaneously build the configuration space and find a path in its discrete representation to the goal. Furthermore, by using an abstraction on groups of robots we dissociate complexity from the number of robots in the group. Although the controllers are designed for navigation in known environments, they are indeed more versatile, as we demonstrate in a concluding simulation of six robots in a partially unknown environment with evolving communication links, object manipulation, and stigmergic interactions

    Flat systems, equivalence and trajectory generation

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    Flat systems, an important subclass of nonlinear control systems introduced via differential-algebraic methods, are defined in a differential geometric framework. We utilize the infinite dimensional geometry developed by Vinogradov and coworkers: a control system is a diffiety, or more precisely, an ordinary diffiety, i.e. a smooth infinite-dimensional manifold equipped with a privileged vector field. After recalling the definition of a Lie-Backlund mapping, we say that two systems are equivalent if they are related by a Lie-Backlund isomorphism. Flat systems are those systems which are equivalent to a controllable linear one. The interest of such an abstract setting relies mainly on the fact that the above system equivalence is interpreted in terms of endogenous dynamic feedback. The presentation is as elementary as possible and illustrated by the VTOL aircraft

    A Framework for Collaborative Multi-task, Multi-robot Missions

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    Robotics is a transformative technology that will empower our civilization for a new scale of human endeavors. Massive scale is only possible through the collaboration of individual or groups of robots. Collaboration allows specialization, meaning a multirobot system may accommodate heterogeneous platforms including human partners. This work develops a unified control architecture for collaborative missions comprised of multiple, multi-robot tasks. Using kinematic equations and Jacobian matrices, the system states are transformed into alternative control spaces which are more useful for the designer or more convenient for the operator. The architecture allows multiple tasks to be combined, composing tightly coordinated missions. Using this approach, the designer is able to compensate for non-ideal behavior in the appropriate space using whatever control scheme they choose. This work presents a general design methodology, including analysis techniques for relevant control metrics like stability, responsiveness, and disturbance rejection, which were missing in prior work. Multiple tasks may be combined into a collaborative mission. The unified motion control architecture merges the control space components for each task into a concise federated system to facilitate analysis and implementation. The task coordination function defines task commands as functions of mission commands and state values to create explicit closed-loop collaboration. This work presents analysis techniques to understand the effects of cross-coupling tasks. This work analyzes system stability for the particular control architecture and identifies an explicit condition to ensure stable switching when reallocating robots. We are unaware of any other automated control architectures that address large-scale collaborative systems composed of task-oriented multi-robot coalitions where relative spatial control is critical to mission performance. This architecture and methodology have been validated in experiments and in simulations, repeating earlier work and exploring new scenarios and. It can perform large-scale, complex missions via a rigorous design methodology

    Graph rigidity-based formation control of planar multi-agent systems

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    A multi-agent system is a network of interacting agents that collectively perform a complex task. This dissertation is concerned with the decentralized formation control of multi-agent systems moving in the plane. The formation problem is defined as designing control inputs for the agents so that they form and maintain a pre-defined, planar geometric shape. The focus is on three related problems with increasing level of complexity: formation acquisition, formation maneuvering, and target interception. Three different dynamic models, also with increasing level of complexity, are considered for the motion of the agents: the single-integrator model, the double-integrator model, and the full mechanical dynamic model. Rigid graph theory and Lyapunov theory are the primary tools utilized in this work for solving the aforementioned formation problems for the three models. The backstepping control technique also plays a key role in the cases of the double-integrator and full dynamic models. Starting with the single-integrator model, a basic formation acquisition controller is proposed that is only a function of the relative position of agents in an infinitesimally and minimally rigid graph. A Lyapunov analysis shows that the origin of the inter-agent distance error system is exponentially stable. It is then shown how an extra term can be added to the controller to enable formation maneuvering or target interception. The three controllers for the single-integrator model are used as a stepping stone and extended to the double-integrator model with the aid of backstepping. Finally, an actuator-level, formation acquisition control law is developed for multiple robotic vehicles that accounts for the vehicle dynamics. Specifically, a class of underactuated vehicles modeled by Euler-Lagrange-like equations is considered. The backstepping technique is again employed while exploiting the structural properties of the system dynamics. Computer simulations are provided throughout the dissertation to show the proposed control laws in action

    The MDLe Engine -- A Software Tool for Hybrid Motion Control

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    One of the important but often overlooked practical challenges in motion control for robotics and other autonomous machines has to do with the implementation of theoretical tools into software that will allow the system to interact effectively with the physical world. More often than not motion control programs are machine-specific and not reusable, even when the underlying algorithm does not require any changes. The work on Motion Description Languages (MDL) has been an effort to formalize a general-purpose robot programming language that allows one to incorporate both switching logic and differential equations. Extended MDL (MDLe) is a device-independent programming language for hybrid motion control, accommodating hybrid controllers, multi-robot interactions and robot-to-robot communications. The purpose of this paper is to describe the "MDLe engine," a software tool that implements the MDLe language. We have designed a basic compiler/software foundation for writing MDLe code. We provide a brief description of the MDLe syntax, implementation architecture, and functionality. Sample programs are presented together with the results of their execution on a set of physical and simulated mobile robots

    Design of an UAV swarm

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    This master thesis tries to give an overview on the general aspects involved in the design of an UAV swarm. UAV swarms are continuoulsy gaining popularity amongst researchers and UAV manufacturers, since they allow greater success rates in task accomplishing with reduced times. Appart from this, multiple UAVs cooperating between them opens a new field of missions that can only be carried in this way. All the topics explained within this master thesis will explain all the agents involved in the design of an UAV swarm, from the communication protocols between them, navigation and trajectory analysis and task allocation

    Flat systems, equivalence and trajectory generation

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    3rd cycleIntroduction : Control systems are ubiquitous in modern technology. The use of feedback control can be found in systems ranging from simple thermostats that regulate the temperature of a room, to digital engine controllers that govern the operation of engines in cars, ships, and planes, to flight control systems for high performance aircraft. The rapid advances in sensing, computation, and actuation technologies is continuing to drive this trend and the role of control theory in advanced (and even not so advanced) systems is increasing..

    "Path-tracking for car-like and tractor-trailer-like robots"

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    Vehicle's dynamic model -- Path tracking -- Controller design -- An application example -- The case of a car-like robot
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