SGER: A Simulation Platform for Research on Developmental Robotics

提案0750011“用于发展机器人研究的仿真平台”PI: Benjamin J. kuipers德克萨斯大学奥斯汀分校这个项目的目标是从低级传感器输入数据中研究关于物体和动作的高级概念的发展。该项目将采用发展性机器人方法：也就是说，它将使用人工智能/机器人模型来研究如何从智能体自身对其世界的感觉运动经验中学习概念。虽然有可能手工构建其中的一些知识，但这些知识往往是不完整和短暂的。因此，对于一个自主智能体来说，要真正强大地应对现实世界情况的复杂性和多样性——并且能够在更短的机器人实验中做到这一点——它必须能够利用自己对丰富的感觉输入和运动动作的理解来建立自己的模型和概念。在这种模式下，学习开始于基本的发展性学习，以获取和奠定高级概念，然后继续终身学习，以适应世界的变化和机器人自身的能力。这个项目的最初目标是创建一个模拟婴儿机器人模型，然后对其进行评估。一旦婴儿机器人成功，该项目将研究同样的方法是否可以创造出足够高保真的猿类或鸦类模拟模型。

Proposal 0750011"A Simulation Platform, for Research on Developmental Robotics"PI: Benjamin J. KuipersUniversity of Texas at AustinABSTRACTThe goal of this project is to investigate the development of high-level concepts about objects and actions from low-level sensor input data. The project will take a developmental robotics approach: that is, it will use AI/robot models to investigate how concepts can be learned from an agent's own sensorimotor experience with its world. While it is possible to build some of this knowledge by hand, such knowledge tends to be incomplete and short-lived. Thus, for an autonomous agent to cope truly robustly with the complexity and diversity of real-world situations--and to be able to do so in more than short-lived robotic experiments--it is imperative for it to be able to use its own understanding of rich sensory input and motor actions to build its own models and concepts. In this paradigm, learning initiates with basic developmental learning to acquire and ground high-level concepts and then continues with life-long learning to adapt to changes in the world and in the robot's own capabilities. The initial thrust of this project will be to create a simulated baby robot model, which will then be evaluated. Once the baby robot is successful, the project will investigate whether the same methods will allow creation of sufficiently high-fidelity simulated models of apes or corvids (crows).