A novel approach for multiple mobile objects path planning: Parametrization method and conflict resolution strategy

We present a new approach containing two steps to determine conflict-free paths for mobile objects in two and three dimensions with moving obstacles. Firstly, the shortest path of each object is set as goal function which is subject to collision-avoidance criterion, path smoothness, and velocity and acceleration constraints. This problem is formulated as calculus of variation problem (CVP). Using parametrization method, CVP is converted to time-varying nonlinear programming problems (TNLPP) and then resolved. Secondly, move sequence of object is assigned by priority scheme; conflicts are resolved by multilevel conflict resolution strategy. Approach efficiency is confirmed by numerical examples.     

Continuous Viewpoint Planning in Conjunction with Dynamic Exploration for Active Object Recognition

Active object recognition (AOR) aims at collecting additional information to improve recognition performance by purposefully adjusting the viewpoint of an agent. How to determine the next best viewpoint of the agent, i.e., viewpoint planning (VP), is a research focus. Most existing VP methods perform viewpoint exploration in the discrete viewpoint space, which have to sample viewpoint space and may bring in significant quantization error. To address this challenge, a continuous VP approach for AOR based on reinforcement learning is proposed. Specifically, we use two separate neural networks to model the VP policy as a parameterized Gaussian distribution and resort the proximal policy optimization framework to learn the policy. Furthermore, an adaptive entropy regularization based dynamic exploration scheme is presented to automatically adjust the viewpoint exploration ability in the learning process. To the end, experimental results on the public dataset GERMS well demonstrate the superiority of our proposed VP method.     

Other than chance and necessity; intention and purpose by design

Very little success has been enjoyed by decision makers in managing the life threatening problems found in the world today using techniques borrowed from the natural sciences and humanities. New promise, however, can be found in the expanded and transdisciplinary notion of the Systems Approach as developed by C. West Churchman. Using Churchman's work as a base for transdisciplinary inquiry, the new image of the dynamics of complex systems presented in the work of Ilya prigogine and others is brought to bear on the most complex system of all; social systems and the roles played by two types of social system participants; designers and planners. Designers provide the trigger in social systems leading to the dynamic system behavior described by prigogine as bifurcation which leads to rebirth and renewal in complex social systems (progress). However, unlike Prigogine's random perturbation, the designed trigger is full of intent and purpose. The complementary role of the planner is to determine the ideal level of systems performance compared to the actual level of performance and to determine how to more closely approximate the ideal (improvement).     

Mixed Integer Programming Approaches to Treatment Planning for Brachytherapy – Application to Permanent Prostate Implants

Mixed integer programming models and computational strategies developed for treatment planning optimization in brachytherapy are described. The problem involves the designation of optimal placement of radioactive sources (seeds) inside a tumor site. Two MIP models are described. The resulting MIP instances are difficult to solve, due in large part to dense constraint matrices with large disparities in the magnitudes of the nonzero entries. A matrix reduction and approximation scheme is presented as a computational strategy for dealing with the dense matrices. Penalty-based primal heuristic and branching strategies to assist in the solution process are also described. Numerical results are presented for 20 MIP instances associated with prostate cancer cases. Compared to currently used computer-aided planning methods, plans derived via the MIP approach use fewer seeds (20–30 fewer) and needles, and provide better coverage and conformity – measures commonly used to assess the quality of treatment plans. Good treatment plans are returned in 15 CPU minutes, suggesting that incorporation of this MIP-based optimization module into a real-time comprehensive treatment planning system is feasible.     

基于有向图规划的最佳物流路径策略分析及应用

本着重讨论基于有向图规划的最佳物流路径策略分析及应用。通过分析物流结构的一般模型，提出最短路径和关键路径物流策略分析方法，给出具体的分析和计算方法，并举实例加以说明，为解决现代物流结构性中存在的系统设计和运作等问题提供理论依据和技术方法。该方法也适用于其他动态规划问题的研究。     

Evaluation of the applicability of MOSFET detectors in radiotherapy

MOSFET detectors of 1 mVcGy⁻¹ sensitivity were tested for the accuracy of absorbed dose measurements in radiation therapy with the use of photon and electron beams. Before a detector was used in the study, several calibration coefficients were determined to allow for different factors affecting its operation. Then, the detector exposure response was compared with the dose calculated in the anthropomorphic phantom by the Monaco and MasterPlan treatment planning systems. MOSFET detectors were placed inside the phantom during the irradiation. Three different plans for thorax and pelvis areas were studied. The paper presents the differences between planned and MOSFET measured doses delivered to the selected target areas using conventional and IMRT techniques.     

Beyond the LAN: Ethernet’s Evolution into the Public Network

This article details the evolution of Ethernet into Gigabit Ethernet and how this LAN-based technology has undergone major transformations over time. From its data rates and distances to supported media and functionality, Ethernet has greatly improved, enabling it to surmount many of its former limitations and in so doing to expand beyond the LAN into the MAN and now even the WAN. In this article, Pioneer Consulting explores the evolution further by focusing on some of the major technological directions in the Ethernet equipment industry.     

Lower bound on the capacity of distributed MIMO systems with spatially correlated Rician/Lognormal fading

This paper presents an analytic lower bound of ergodic capacity for distributed MIMO (D-MIMO) systems that experience not only Rician fading but also shadowing effects of Lognormal distributed. In particularly, we consider that the Rician fading channel is spatially correlated at both transmitter and receiver. In the communication environment corresponding to this setting, the angle spread at the transmitter and the angle spread at the receiver are both insufficient, and the non-fading components co-exists with the fading components. Such communication environment is very common. In the process of deriving the analytic lower bound, in order to avoid Hayakawa polynomials that cannot be analytically expressed, non-central quadratic forms are transformed to non-central Wishart matrices by use of inequality. The validity of the presented lower bound is verified by computer simulations. The simulation results show the influence of the number of radio ports at the transmitter, the number of antennas at the transmitter or receiver, correlation level (angle spreads) and Rician K-factor on the capacity of systems. In all cases, the presented bound remains tight across the entire signal-to-noise ratio (SNR) regime.     

基于粒子群并行优化的煤矿井下机器人路径规划

路径规划是煤矿井下搜救探测机器人自主导航的关键步骤,矿井是三维的非机构化的环境,机器人行走过程应该具有高度智能的路径规划,传统的自适应能力与处理非线性的问题能力较差,路径规划误差较大,提出基于粒子群并行优化的煤矿井下机器人路径规划方法,充分考虑井下的环境高低变化,采用栅格法对环境建模,将粒子群独立分布在不同容器中分别进行路径建模,不同容器中粒子分别进行优化操作;因为速度和最优子群被分别保留,在机器人路径规划实验阶段,路径规划的时间较传统方法降低20%,避障成功率高达95%,最优路径的出现概率能保持在99%,这种方法具有很强的指导性与实用价值。     

The complexity of the free space for a robot moving amidst fat obstacles

We propose a new definition of fatness of geometric objects and compare it with alternative definitions. We show that, under some realistic assumptions, the complexity of the free space for a robot, with any fixed number of degrees of freedom moving in a d-dimensional Euclidean workspace with fat obstacles, is linear in the number of obstacles. The complexity of motion planning algorithms depends on the complexity of the robot's free space, and theoretically, the complexity of the free space can be very high. Thus, our result opens the way to devising provable efficient motion planning algorithms in certain realistic settings.