1、熟悉工程力学的研究对象、内容, 2、掌握刚体、平衡、力的概念 3、掌握五个公理 ▪ 绪论 ▪ §1-1 刚体和力的概念 ▪ §1-2 静力学公理 ❑ §1-3 力矩 ❑ §1-4 力偶 ❑ §1-5 力的平移 1、常见的几种约束及其约束力的画法 2、物体及物系的受力图 ▪ §2-1 约束与约束反力 ▪ §2-2 受力图 ❑ 力系合成的解析法 ▪ 力在直角坐标轴上的投影 ▪ 合力投影定理 ❑ 平面任意力系的简化 ▪ 简化方法 ▪ 结果讨论 ❑ 平面任意力系平衡方程 ❑ 问题举例 ❑ 物体系统平衡 ▪ 物体系物体的数量和平衡方程个数 ▪ 物体系统问题求解原则 ❑ 静定和静不定问题 ❑ 摩擦 ❑ 空间问题 ❑ 空间任意力系的平衡方程 ❑ 重心 ❑ 问题举例

主要内容 一、工程中承受切应力的构件 二、扭转内力—扭矩 三、扭转切应力分析与计算

Foundations of state Estimation Topics: Bayes Filters Kalman filters Hidden markov models Additional readins G. Welch and G. Bishop. An Introduction to the Kalman Filter \. University of North Carolina at Chapel Hill

Conflicts and Kernel Diagnoses Generating Kernels from Conflicts Finding Consistent Modes Estimating Likely Modes Conflict-directed

Brian C Williams, copyright 2000 Mode estimation Mode reconfiguration Select a most likely set of Select a least cost set of component modes that are commandable component consistent with the model and modes that entail the current observations

Hybrid Mode Estimation and Gaussian Filtering with Hybrid HMMs Stanislav funiak 16. 412/6.834 Lecture, 15 March 2004 References Hofbaur, M. W, and Williams, B C(2002). Mode estimation of probabilistic hybrid systems. In: Hybrid Systems: Computation and Control Hscc 2002 Funiak, S, and Williams, B. C (2003 ). Multi-modal particle filtering for hybrid systems with autonomous mode transitions. In: DX-2003 SafeProcess 2003 Lerner, U.,R. Parr, D. Koller and G. Biswas(2000). Bayesian fault detection and diagnosis in dynamic

Readings in Planning as Forward Heuristic Search \The FF Planning System: Fast Plan Generation Through Heuristic Search,\ by Jorg Hoffmann and Bernhard Nebel, Journal of Artificial Intelligence Research, 2001. “Planning as Heuristic Search,\ by Blai Bonet and Hector Geffner, Artificial

Cognitive Robotics Outline Temporal Action Graph Walksat: Stochastic Local Search Better Neighbor Relaxed Plan A. Gerevini, A. Saetti, I. Serina \Planning through Stochastic Local Search and Temporal Action Graphs\, to appear in Journal of Artificial Intelligence

Massachusetts Institute of Technology 16.412/6.834 Cognitive Robotics Distributed: Monday, 3/31/04 Objective The purpose of the following handout is to walk you step by step through the execution of the FF planning algorithm, on a simple example. The FF algorithm is presented in the paper:

Outline Model-based programming The need for model-based reactive planning The Burton model-based reactive planner Artificial Intelligence Space Systems