论文标题
需要用于机器人自主权的元结构
The Need for a Meta-Architecture for Robot Autonomy
论文作者
论文摘要
机器人系统的长期自主权隐含地需要可靠的平台，这些平台能够自然处理硬件和软件故障，行为问题或缺乏知识。基于模型的可靠平台还需要在系统开发过程中应用严格的方法，包括使用正确的构造技术来实现机器人行为。随着机器人的自治水平的提高，提供系统可靠性的提供成本也会增加。我们认为，自主机器人的可靠性可靠性可以从几种认知功能，知识处理，推理和元评估的正式模型中受益。在这里，我们为自主机器人代理的认知体系结构的生成模型提出了案例，该模型订阅了基于模型的工程和可靠性，自主计算和知识支持机器人技术的原理。
Long-term autonomy of robotic systems implicitly requires dependable platforms that are able to naturally handle hardware and software faults, problems in behaviors, or lack of knowledge. Model-based dependable platforms additionally require the application of rigorous methodologies during the system development, including the use of correct-by-construction techniques to implement robot behaviors. As the level of autonomy in robots increases, so do the cost of offering guarantees about the dependability of the system. Certifiable dependability of autonomous robots, we argue, can benefit from formal models of the integration of several cognitive functions, knowledge processing, reasoning, and meta-reasoning. Here we put forward the case for a generative model of cognitive architectures for autonomous robotic agents that subscribes to the principles of model-based engineering and certifiable dependability, autonomic computing, and knowledge-enabled robotics.
