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The Accompanying Behavior Model and Implementation Architecture of Autonomous Robot Software

机译：自主机器人软件的伴随行为模型与实现架构

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Autonomous robots are increasingly applied in realworld environments, and expect to execute plans robustly to accomplish the assigned tasks in the presence of dynamics and uncertainties of the changing environment. The robustness of plan execution requires the robot to keep aware of plan execution status and to adapt the plan towards possible execution contingencies. Such requirements pose a great challenge for autonomous robot software in terms of the abstraction model over robot behavior patterns. Conventional abstraction models for robot behaviors generally follow the sense-model-planact and behavior-based paradigms, which show limitations in tight integration with sensory inputs and tracking execution traces of robot plans. This paper proposes an accompanying behavior model that considers robot behaviors as task-oriented and observation-based types with diverse aims, and develops the run-time mechanisms to facilitate collaboration between two types of behaviors. Additionally, we implement the model by the multi-agent approach which develops the robot software as a multi-agent system. To demonstrate the feasibility and applicability of proposed model, we conduct a case study by implementing a typical example of service scenarios, e.g., a robot that autonomously picks up and drops off dishes for remote guests in the open and dynamic environment.
机译：自主机器人越来越多地应用在现实环境中，并期望在存在动态和不确定的环境变化的情况下稳健地执行计划，以完成分配的任务。计划执行的鲁棒性要求机器人保持对计划执行状态的了解，并使计划适应可能的执行突发事件。就相对于机器人行为模式的抽象模型而言，这样的要求对自主机器人软件提出了巨大的挑战。机器人行为的常规抽象模型通常遵循感官模型计划和基于行为的范式，这在与感官输入紧密集成以及跟踪机器人计划的执行轨迹方面显示出局限性。本文提出了一个伴随的行为模型，该模型将机器人行为视为具有多种目标的面向任务和基于观察的类型，并开发了运行时机制来促进两种行为之间的协作。此外，我们通过多主体方法实施模型，该方法将机器人软件开发为多主体系统。为了证明所提出模型的可行性和适用性，我们通过实施服务场景的典型示例进行案例研究，例如，一个机器人可以在开放和动态的环境中自动为远程宾客取菜。

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