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针对现有基于粒子群参数优化的改进蚁群算法耗时较大的问题,提出了一种新的解决方案.方案中采用一种全局异步与精英策略相结合的信息素更新方式,同时合理减少蚁群算法被粒子群算法调用一次所需的迭代代数.对日本旭川垃圾场巡查机器人路径规划问题仿真求解的结果表明,与其他算法相比,该改进算法具有比较明显的速度优势
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Outline Path Planning in Partially Known Environments. Finding the Shortest Path to the Goal. Alternative Approaches to Path Planning in Partially Known Environments. Continuous Optimal Path Planning
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Probabilistic roadmaps Planning in the real world Planning amidst moving obstacles RRT-based planners Conclusions Applicability of Lazy PRM to Spheres
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Foundations of State Estimation PartⅡ Topics: Hidden Markov Models Particle Filters Additional reading: L. R. Rabiner, \ tutorial on hidden Markoy models,\ Proceedings of the IEEE, vol. 77,. 257-286, 1989 Radford M. Neal, 1993. Probabilistic Inference Using Markov Chain Monte
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Temporal Planning in Space Brian C. Williams 16.412J/6.834J based on \Handling Time: February 23rd, 2004 Constraint-based Interval Planning,\ by David E. Smith Outline Operational Planning for the Mars Exploration Rovers
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Fault Aware Systems: Model-based Programming and Diagnosis Brian C. Williams 16.412J/6.834J March 8th, 2004 courtesy of JPL Four launches in 7 months MERS CSAIL
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人工势场法是一种简单有效的移动机器人路径规划算法.针对传统人工势场法在路径规划中的一类目标点不可达问题,提出了一种在局部最小点改变斥力角度和设定虚拟最小局部区域的解决方案,同时采用遗传算法对改进算法中斥力改变角度以及虚拟最小局部区域的半径两个参数进行优化.仿真实验说明本文所提算法能在起点和终点之间规划出一条简捷、光滑和安全的路径
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Mapping Topics: Topological Maps SLAM HMMs Revisited Additional reading: B. J. Kuipers Y.-T. Byun. 1991. \A robot exploration and mapping strategy based on a semantic hierarchy of spatial rep rstations. jour. s and
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Model-based Diagnosis a failure is a discrepancy between the model and observations of an artifact a diagnosis restores consistency 1. Enumerate candidates in order of likelihood
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Using the Forest to See the Trees: Context-based Object Recognition Bill Freeman Joint work with Antonio Torralba and Kevin Murphy Computer Science and Artificial Intelligence Laboratory MIT computer vision goal Recognize many different objects under many viewing conditions in unconstrained settings
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