Learning and Intelligent Systems: Learning Minimal Representations for Visual Navigation and Recognition

该项目是通过学习和智能系统（LIS）计划资助的。该项目关注的是在有机体和机器的感觉运动活动和认知能力（如推理、计划和学习）之间的相互作用中表现出的智力。这种相互作用经常表现在导航行为中，人类和其他动物从小就参与其中，此后在正常情况下几乎毫不费力。无论导航是天生的还是后天习得的，重要的是要努力理解各种认知、感知和运动系统之间的相互作用。这些相互作用的复杂性在移动机器人的发展中变得清晰起来，比如最近部署在火星上的机器人，更不用说未来计划的更自主的机器人了。创建程序来协调传感器，保持该区域的内部地图，并允许机器人有效地穿越空间，而不会与障碍物发生碰撞，这仍然是一项主要的、尚未完全理解的任务。本研究项目采用跨学科的方法，通过实验探索人类的能力，根据实验结果和人类导航的已知知识开发模型，将这些模型实现在机器人控制程序中，然后在机器人导航实验中测试这些程序作为人类导航模型的有效性和合理性。目标是了解人类和机器的现象，并开发用于移动机器人的鲁棒算法。这个由研究心理物理学、认知、计算和机器人技术的研究人员组成的联盟将导致许多学科的知识增长，并将增强我们对人工和自然代理的空间认知和视觉导航的理解。

This project is being funded through the Learning and Intelligent Systems (LIS) initiative. The project is concerned with the intelligence exhibited in interactions among sensory-motor activities and cognitive capacities such as reasoning, planning and learning, in both organisms and machines. Such interaction is regularly shown in the act of navigation, which is engaged in by humans and other animals from an early age, and seems almost effortless in normal circumstances thereafter. Whatever there is in navigation that is innate and whatever is learned, it is important to try to understand the interaction of the various cognitive, perceptual, and motor systems that are involved. The complexity of these interactions becomes clear in the development of mobile robots, such as the one recently deployed on Mars, not to mention the more autonomous ones planned for the future. It is still a major and imperfectly understood task to create programs that will coordinate sensors, keep an internal emapn of the area, and allow the robot to cross a space efficiently and without collisions with obstacles. An interdisciplinary approach is being taken in this research project, exploring human capabilities through experiments, developing models based on the experimental results and what is already known about human navigation, implementing these models in programs for robot control, then testing these programs in robotic navigation experiments for their efficacy and their reasonableness as models of human navigation. The goals are both to understand the phenomena in humans and machines and to develop robust algorithms to be used in mobile robots. This alliance of researchers studying psychophysics, cognition, computation, and robotics will lead to gains in knowledge across many disciplines and will enhance our understanding of spatial cognition and visual navigation in agents, both artificial and natural.