Collaborative Research: Motion -- Models, Algorithms, and Complexity

Pankaj ArgarwalDuke University Collaborative0204118/0204486运动与形状一样，是在计算机中表示和操纵物理世界而要建模的基本形态之一。因此，运动表示及其算法是处理物理对象的所有计算学科的核心：计算机图形学、计算机视觉、机器人学等。运动建模对于处理时间变化的数据的其他学科也是至关重要的，包括移动网络、时态数据库等。运动算法需要计算资源，还需要频繁的感知和通信资源来完成它们的任务。尽管运动在许多计算机学科中扮演着重要的角色，但到目前为止，还没有做什么工作来提供一个清晰的概念框架来表示运动，描述运动对象的算法，并分析它们的行为和性能。这项提议的目标是推动计算机科学表示和算法的前沿，这些表示和算法处理各种形式的运动。其目的是为获取、建模、推理、规划、操纵或执行运动及其相关的复杂性度量的过程创建可靠的算法理论。

Pankaj ArgarwalDuke UniversityCollaborative0204118/0204486Motion, like shape, is one of the fundamental modalities to be modeled in order to represent and manipulate the phys-ical world in a computer. As such, motion representations and the algorithms that operate on them are central to all computational disciplines dealing with physical objects: computer graphics, computer vision, robotics, etc. Mod-eling motion is also crucial for other disciplines dealing with temporally varying data, including mobile networks, temporal databases, etc. Motion algorithms require com-putationalresources, and frequently sensing and commu-nication resources as well, in order to accomplish theirtask. Despite the prominent position that motion plays in so many computer disciplines, little has been done to date to provide a clean conceptual framework for representing motion, describing algorithms on moving objects, and an-alyzing their behavior and performance. It is the goal of this proposal to push the frontiers of the computer sci-ence representations and algorithms that deal with motion in its various manifestations. The aim is to create a firm algorithmic theory for the processes of acquiring, model-ing, reasoning about, planning, manipulating, or executing motion and their relevant complexity measures.