公开(公告)号：US20120209652A1

公开(公告)日：2012-08-16

申请号：US13069638

申请日：2011-03-23

申请人： Deepak Khosla ,  Eric Huang ,  David L. Ii

发明人： Deepak Khosla ,  Eric Huang ,  David L. Ii

IPC分类号： G06Q10/00

CPC分类号： G06Q10/0631

摘要： To improve the scheduling and tasking of resources, the present disclosure describes an improved planning system and method for the allocation and management of resources. The planning system uses a branch and bound approach of tasking resources using a heuristic to expedite arrival at a deterministic solution. For each possible functional mode of the resources, an upper bound is determined. The upper bounds are employed in an objective function for the branch and bound process to determine the functional mode in which to place the resources and to determine movement paths for the resources, all in an environment where a hostile force may attempt to destroy the resources.

摘要翻译： 为了改进资源的调度和任务，本公开描述了一种用于资源分配和管理的改进的规划系统和方法。 规划系统使用启发式方法使用分支和绑定的任务资源方法来加速到达确定性解决方案。 对于资源的每个可能的功能模式，确定上限。 上限用于分支和绑定过程的目标函数，以确定放置资源的功能模式，并确定资源的移动路径，所有这些都在敌对力量可能试图破坏资源的环境中。

公开(公告)号：US08396730B2

公开(公告)日：2013-03-12

申请号：US13069638

申请日：2011-03-23

申请人： Deepak Khosla ,  Eric Huang ,  David L. Ii

发明人： Deepak Khosla ,  Eric Huang ,  David L. Ii

IPC分类号： G06Q10/00

CPC分类号： G06Q10/0631

摘要： To improve the scheduling and tasking of resources, the present disclosure describes an improved planning system and method for the allocation and management of resources. The planning system uses a branch and bound approach of tasking resources using a heuristic to expedite arrival at a deterministic solution. For each possible functional mode of the resources, an upper bound is determined. The upper bounds are employed in an objective function for the branch and bound process to determine the functional mode in which to place the resources and to determine movement paths for the resources, all in an environment where a hostile force may attempt to destroy the resources.

摘要翻译： 为了改进资源的调度和任务，本公开描述了一种用于资源分配和管理的改进的规划系统和方法。 规划系统使用启发式方法使用分支和绑定的任务资源方法来加速到达确定性解决方案。 对于资源的每个可能的功能模式，确定上限。 上限用于分支和绑定过程的目标函数，以确定放置资源的功能模式，并确定资源的移动路径，所有这些都在敌对力量可能试图破坏资源的环境中。

公开(公告)号：US08634982B2

公开(公告)日：2014-01-21

申请号：US12543665

申请日：2009-08-19

申请人： Deepak Khosla ,  David Fuciarelli ,  David L Ii

发明人： Deepak Khosla ,  David Fuciarelli ,  David L Ii

IPC分类号： G05D1/00

CPC分类号： G05D1/104

摘要： To improve the scheduling and tasking of sensors, the present disclosure describes an improved planning system and method for the allocation and management of sensors. In one embodiment, the planning system uses a branch and bound approach of tasking sensors using a heuristic to expedite arrival at a deterministic solution. In another embodiment, a progressive lower bound is applied to the branch and bound approach. Also, in another embodiment, a hybrid branch and bound approach is used where both local and global planning are employed in a tiered fashion.

摘要翻译： 为了改进传感器的调度和任务，本公开描述了用于分配和管理传感器的改进的规划系统和方法。 在一个实施例中，规划系统使用启发式方法使用任务传感器的分支和绑定方法来加速到达确定性解决方案。 在另一个实施例中，渐进下界应用于分支和绑定方法。 此外，在另一个实施例中，使用混合分支和绑定方法，其中以分层方式采用本地和全局规划。

公开(公告)号：US20110046837A1

公开(公告)日：2011-02-24

申请号：US12543665

申请日：2009-08-19

申请人： Deepak Khosla ,  David Fuciarelli ,  David L. Ii

发明人： Deepak Khosla ,  David Fuciarelli ,  David L. Ii

IPC分类号： G05D1/00

CPC分类号： G05D1/104

摘要： To improve the scheduling and tasking of sensors, the present disclosure describes an improved planning system and method for the allocation and management of sensors. In one embodiment, the planning system uses a branch and bound approach of tasking sensors using a heuristic to expedite arrival at a deterministic solution. In another embodiment, a progressive lower bound is applied to the branch and bound approach. Also, in another embodiment, a hybrid branch and bound approach is used where both local and global planning are employed in a tiered fashion.

摘要翻译： 为了改进传感器的调度和任务，本公开描述了用于分配和管理传感器的改进的规划系统和方法。 在一个实施例中，规划系统使用启发式方法使用任务传感器的分支和绑定方法来加速到达确定性解决方案。 在另一个实施例中，渐进下界应用于分支和绑定方法。 此外，在另一个实施例中，使用混合分支和绑定方法，其中以分层方式采用本地和全局规划。

公开(公告)号：US08699767B1

公开(公告)日：2014-04-15

申请号：US12975352

申请日：2010-12-21

申请人： Deepak Khosla ,  David J. Huber ,  Rajan Bhattacharyya

发明人： Deepak Khosla ,  David J. Huber ,  Rajan Bhattacharyya

IPC分类号： G06K9/00

CPC分类号： G06K9/6267 ,  G06K9/00496 ,  G06K9/4609 ,  G06K9/6212 ,  G06K9/626 ,  G06T7/215

摘要： Described is a system for optimizing rapid serial visual presentation (RSVP). A similarity metric is computed for RSVP images, and the images are sequenced according to the similarity metrics. The sequenced images are presented to a user, and neural signals are received to detect a P300 signal. A neural score for each image is computed, and the system is optimized to model the neural scores. The images are resequenced according a predictive model to output a sequence prediction which does not cause a false P300 signal. Additionally, the present invention describes computing a set of motion surprise maps from image chips. The image chips are labeled as static or moving and prepared into RSVP datasets. Neural signals are recorded in response to the RSVP datasets, and an EEG score is computed from the neural signals. Each image chip is then classified as containing or not containing an item of interest.

摘要翻译： 描述了一种用于优化快速串行视觉呈现（RSVP）的系统。 为RSVP图像计算相似性度量，并且根据相似性度量对图像进行排序。 将序列图像呈现给用户，并且接收神经信号以检测P300信号。 计算每个图像的神经分数，并优化系统以对神经分数进行建模。 根据预测模型对图像进行重新排序，以输出不引起假P300信号的序列预测。 另外，本发明描述了从图像芯片计算一组运动惊喜图。 图像芯片被标记为静态或移动并准备成RSVP数据集。 根据RSVP数据集记录神经信号，并根据神经信号计算EEG得分。 然后将每个图像芯片分类为包含或不包含感兴趣的项目。

公开(公告)号：US08396282B1

公开(公告)日：2013-03-12

申请号：US12262548

申请日：2008-10-31

申请人： David J Huber ,  Deepak Khosla ,  Paul Alex Dow

发明人： David J Huber ,  Deepak Khosla ,  Paul Alex Dow

IPC分类号： G06K9/00 ,  G05B15/00

CPC分类号： G06K9/4623 ,  G06K9/629

摘要： The present disclosure describes a fused saliency map from visual and auditory saliency maps. The saliency maps are in azimuth and elevation coordinates. The auditory saliency map is based on intensity, frequency and temporal conspicuity maps. Once the auditory saliency map is determined, the map is converted into azimuth and elevation coordinates by processing selected snippets of sound from each of four microphones arranged on a robot head to detect the location of the sound source generating the saliencies.

摘要翻译： 本公开描述了来自视觉和听觉显着图的融合显着图。 显着图是方位角和高程坐标。 听觉显着图基于强度，频率和时间显着性图。 一旦听觉显着性图被确定，通过处理布置在机器人头上的四个麦克风中的每一个的选定的声音片段来检测产生出色的声源的位置，将地图转换成方位角和仰角坐标。

公开(公告)号：US08010658B2

公开(公告)日：2011-08-30

申请号：US12027588

申请日：2008-02-07

申请人： Deepak Khosla ,  James Guillochon ,  Howard C. Choe

发明人： Deepak Khosla ,  James Guillochon ,  Howard C. Choe

IPC分类号： G06F15/173

CPC分类号： G06K9/6292 ,  G06K9/3241 ,  G06K2009/3291 ,  G06T7/277

摘要： According to one embodiment, a computing system includes a computing node coupled to a number of sensors. The sensors are operable to generate records from received information and transmit these records to the computing node. The computing node is operable to bind the plurality of records in a plurality of classifications using a multiple level classifier such that each classification has a differing level of specificity.

摘要翻译： 根据一个实施例，计算系统包括耦合到多个传感器的计算节点。 传感器可操作以从接收到的信息生成记录，并将这些记录传送到计算节点。 计算节点可操作以使用多级分类器来以多个分类结合多个记录，使得每个分类具有不同的特异性水平。

公开(公告)号：US20080255911A1

公开(公告)日：2008-10-16

申请号：US11786906

申请日：2007-04-13

申请人： Deepak Khosla

发明人： Deepak Khosla

IPC分类号： G06F9/46

CPC分类号： H04L67/125 ,  G01S5/0294 ,  G06Q10/0639

摘要： A method and system provide closed loop management control of multiple sensors that receive kinematic, classification and search measurement inputs regarding targets being tracked by the sensors during a measurement cycle in addition to performance requirements inputs. The kinematic, classification and search needs and gains are computed by the system resulting in corresponding entropy outputs which are combined to provide outputs defining joint information need and gains. Based on the joint information need and gains outputs, the system pairs each track with a possible sensor for making measurements during the next measurement cycle and repeats the process this process until all performance goals have been achieved for optimally satisfying the information need requirements for accurate target detection, tracking and classification.

摘要翻译： 一种方法和系统提供多个传感器的闭环管理控制，该传感器接收运动学，分类和搜索测量输入，以便在测量周期内除了性能要求输入之外，还可以在测量周期内由传感器跟踪目标。 运动学，分类和搜索需求和收益由系统计算得到相应的熵输出，它们被组合以提供定义联合信息需求和收益的输出。 基于联合信息需求和增益输出，系统将每个轨道与可能的传感器配对，用于在下一个测量周期内进行测量，并重复该过程，直到达到所有性能目标，以最佳地满足信息需求为准确目标 检测，跟踪和分类。

公开(公告)号：US20060242099A1

公开(公告)日：2006-10-26

申请号：US11111359

申请日：2005-04-20

申请人： Yang Chen ,  Deepak Khosla

发明人： Yang Chen ,  Deepak Khosla

IPC分类号： G06N5/02

CPC分类号： G06N5/046

摘要： A sensitivity analysis method is built upon a PAS framework that includes a knowledge base defined by a set of propositions, a set of logical statements over the propositions, a set of assumptions for each statement and the corresponding assumption probabilities. The knowledge base is queried to determine the quasi-support qs(H) and qs(⊥). Disjoint arguments of the quasi-support are then found for both the hypothesis H and contradiction ⊥. Symbolic formulas dqs(H) and dqs(⊥) are formed for the degree of quasi-support for hypothesis H and contradiction ⊥, respectively, based on these disjoint arguments. The partial derivatives D H , j ≡ ∂ dqs ⁡ ( H ) ∂ r j ⁢   ⁢ of ⁢   ⁢ dqs ⁡ ( H ) ⁢   ⁢ and ⁢   ⁢ D ⊥ , j ≡ ∂ dqs ⁡ ( ⊥ ) ∂ r j of dqs(⊥) are computed with respect to the assumption probability rj. Sensitivity analysis formulas ƒ(H,DH,j,D⊥,j,rj,δrj) are then formed from the partial derivatives to establish the relationship between a PAS output, such as the degree of support dsp( ), degree of doubt ddb( ), and degree of possibility dps( ), for hypothesis H, and the assumption probabilities under a given input condition. The formulas can be used to determine how to tune the assumption probabilities to achieve the desired PAS output values, to identify key assumption probabilities, to measure the sensitivity of the system to the assumption probabilities, to account for input variability, to identify contradictions in the knowledge base and so forth.

公开(公告)号：US06751547B2

公开(公告)日：2004-06-15

申请号：US09994515

申请日：2001-11-26

申请人： Deepak Khosla

发明人： Deepak Khosla

IPC分类号： G01C2132

CPC分类号： G01C21/26 ,  G01S7/411 ,  G01S13/867

摘要： A method and apparatus for accurate estimation of forward path geometry of a vehicle based on a two-clothoid road model are presented. Road data provided by a camera or a radar system is collected 200 and a full measurement transfer function of the two-clothoid model is computed 202. The near-range and the far-range clothoid coefficients are estimated simultaneously 204; and the forward path of the vehicle is estimated using the data provided by the two-clothoid model 206.

摘要翻译： 提出了一种基于双回旋道路模型准确估计车辆前进路径几何的方法和装置。 收集由相机或雷达系统提供的道路数据，并计算出二回旋模型的完整测量传递函数202.近距离和远程回旋系数同时估计204; 并且使用由双回旋模型206提供的数据来估计车辆的前进路径。