Constraint-based agents

该研究计划的目标是开发建筑智能系统的原则和实践。我们正在开发一个正式的理论，设计和实施基于约束的代理，包括机器人。我们的基于约束的代理（CBA）框架是一套理论和实践的工具，用于设计嵌入在主动环境中的代理控制器。我们将在几个新的方向上发展这个模型。首先，我们计划将学习技术纳入CBA。其次，我们将允许与人类教师进行互动。第三，我们将研究多机器人区域探索的算法。第四，我们计划纳入各种技术阐述，以扩展模型的功能。我们已经开发了一个位置感知辅助轮椅使用个人，支持路线规划和导航在室内和室外环境。我们计划将导航系统与用户的个人调度系统相结合，一起解决空间和时间约束。我们最近还开发了一种智能机器人动力轮椅原型，它可以同时使用航位推算、视觉和其他传感器进行自我定位，绘制环境地图，并主动避开静态和动态障碍物。我们还打算将这两个系统整合到一个平台上。椅子使用者的初始目标人群包括长期护理设施中的轻度至中度认知障碍用户。这些系统的试验正在计划在不久的将来，与我们的合作者在温哥华和多伦多。我们最近还开发了一个基于约束的城市规划系统，采用多点触摸桌面，将可持续性约束纳入其中。我们计划扩展这个系统，允许多个用户和自动约束求解器的约束的协作解决方案。CBA方法的科学新奇源于其形式基础，实用性和简单性，作为一个单一的混合智能系统作为代理的理论。实际工程意义在于，我们现在可以使用这些工具构建更安全、更可靠的基于约束的人工制品。

The goal of this research program is to develop the principles and practices of building intelligent systems. We are developing a formal theory for the design and implementation of constraint-based agents, including robots. Our Constraint-Based Agent (CBA) framework is a set of theoretical and practical tools for designing controllers for agents embedded in an active environment. We shall develop the model in several new directions. First, we plan to incorporate learning techniques into CBA. Second, we will allow interaction with a human teacher. Third, we will work on algorithms for multi-robot area exploration. Fourth, we plan to incorporate various technical elaborations to extend the power of the model. We have developed a location-aware aid for wheelchair-using individuals that supports route planning and navigation in indoor and outdoor environments. We plan to couple the navigation system with the user's personal scheduling system, solving both spatial and temporal constraints together. We have also recently developed a prototype intelligent robotic power wheelchair that can simultaneously self-localize, using dead-reckoning, vision and other sensors, map its environment and actively avoid static and dynamic obstacles. We also intend to integrate these two systems on a single platform. The initial target population of chair users consists of mild-to-moderately cognitively impaired users in long-term care facilities. Trials for these systems are being planned for the near future, with our collaborators in Vancouver and Toronto. We have also recently developed a constraint-based system for urban planning, incorporating sustainability constraints, using a multi-touch table surface. We plan to extend this system to allow collaborative solution of the constraints by several users and an automated constraint solver. The scientific novelty of the CBA approach stems from its formal foundation, its practicality and its simplicity as a unitary theory of hybrid intelligent systems as agents. The practical engineering significance is that we can now build safer and more reliable constraint-based artefacts using these tools.