Abstract-We present a stable control strategy for groups of vehicles to move and reconfigure cooperatively in response to a sensed, distributed environment. Each vehicle in the group serves as a mobile sensor and the vehicle network as a mobile and reconfigurable sensor array. Our control strategy decouples, in part, the cooperative management of the network formation from the network maneuvers. The underlying coordination framework uses virtual bodies and artificial potentials. We focus on gradient climbing missions in which the mobile sensor network seeks out local maxima or minima in the environmental field. The network can adapt its configuration in response to the sensed environment in order to optimize its gradient climb.
Abstract-Behavior Trees (BTs) is a way of organizing the switching structure of a Hybrid Dynamical System (HDS), that was originally introduced in the computer game programming community.In this paper, we analyze how the BT representation increases the modularity of a HDS, and how key system properties are preserved over compositions of such systems, in terms of combining two BTs into a larger one. We also show how BTs can be seen as a generalization of Sequential Behavior Compositions, the Subsumption Architecture and Decisions Trees. These three tools are powerful, but quite different, and the fact that they are unified in a natural way in BTs might be a reason for their popularity in the gaming community. We conclude the paper by giving a set of examples illustrating how the proposed analysis tools can be applied to robot control BTs.
Abstract-This paper presents a unified framework for Behavior Trees (BTs), a plan representation and execution tool. The available literature lacks the consistency and mathematical rigor required for robotic and control applications. Therefore, we approach this problem in two steps: first, reviewing the most popular BT literature exposing the aforementioned issues; second, describing our unified BT framework along with equivalence notions between BTs and Controlled Hybrid Dynamical Systems (CHDSs). This paper improves on the existing state of the art as it describes BTs in a more accurate and compact way, while providing insight about their actual representation capabilities. Lastly, we demonstrate the applicability of our framework to real systems scheduling open-loop actions in a grasping mission that involves a NAO robot and our BT library.
Abstract-In this paper, the multiagent coordination problem is studied. This problem is addressed for a class of robots for which control Lyapunov functions can be found. The main result is a suite of theorems about formation maintenance, task completion time, and formation velocity. It is also shown how to moderate the requirement that, for each individual robot, there exists a control Lyapunov function. An example is provided that illustrates the soundness of the method.
In this paper, we argue that the modularity, reusability and complexity of Unmanned Aerial Vehicle (UAV) guidance and control systems might be improved by using a Behavior Tree (BT) architecture. BTs are a particular kind of Hybrid Dynamical Systems (HDS), where the state transitions of the HDS are implicitly encoded in a tree structure, instead of explicitly stated in transition maps. In the gaming industry, BTs have gained a lot of interest, and are now replacing HDS in the control architecture of many automated in-game opponents. Below, we explore the relationship between HDS and BTs. We show that any HDS can be written as a BT and that many common UAV control constructs are quite naturally formulated as BTs. Finally, we discuss the positive implications of making the above mentioned state transitions implicit in the BTs.
Abstract-In this paper, the multiagent coordination problem is studied. This problem is addressed for a class of robots for which control Lyapunov functions can be found. The main result is a suite of theorems about formation maintenance, task completion time, and formation velocity. It is also shown how to moderate the requirement that, for each individual robot, there exists a control Lyapunov function. An example is provided that illustrates the soundness of the method.
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