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

该项目由学习和智能系统倡议资助。该项目关注的是在生物体和机器的感觉运动活动和认知能力（如推理、规划和学习）之间的相互作用中表现出的智能。 这种相互作用经常表现在导航行为中，这是人类和其他动物从小就从事的活动，在此后的正常情况下似乎几乎毫不费力。 无论导航中有什么是先天的，也无论是后天习得的，重要的是要努力理解所涉及的各种认知、知觉和运动系统的相互作用。这些互动的复杂性在移动的机器人的开发中变得清晰起来，比如最近部署在火星上的机器人，更不用说计划在未来开发的更加自主的机器人了。 这仍然是一个主要的和不完全理解的任务，创造程序，将协调传感器，保持一个内部emapn的区域，并允许机器人跨越空间有效地和没有碰撞的障碍。 在这个研究项目中，正在采取跨学科的方法，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，在机器人控制程序中实现这些模型，然后在机器人导航实验中测试这些程序的有效性和合理性作为人类导航模型。 目标是了解人类和机器的现象，并开发用于移动的机器人的鲁棒算法。研究心理物理学，认知，计算和机器人技术的研究人员的联盟将导致许多学科的知识增益，并将增强我们对人工和自然代理中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.