Topology-Guided Path Integral Approach for Stochastic Optimal Control in Cluttered Environment

This paper addresses planning and control of robot motion under uncertainty that is formulated as a continuous-time, continuous-space stochastic optimal control problem, by developing a topology-guided path integral control method. The path integral control framework, which forms the backbone of the proposed method, re-writes the Hamilton-Jacobi-Bellman equation as a statistical inference problem; the resulting inference problem is solved by a sampling procedure that computes the distribution of controlled trajectories around the trajectory by the passive dynamics. For motion control of robots in a highly cluttered environment, however, this sampling can easily be trapped in a local minimum unless the sample size is very large, since the global optimality of local minima depends on the degree of uncertainty. Thus, a homology-embedded sampling-based planner that identifies many (potentially) local-minimum trajectories in different homology classes is developed to aid the sampling process. In combination with a receding-horizon fashion of the optimal control the proposed method produces a dynamically feasible and collision-free motion plans without being trapped in a local minimum. Numerical examples on a synthetic toy problem and on quadrotor control in a complex obstacle field demonstrate the validity of the proposed method.Comment: arXiv admin note: text overlap with arXiv:1510.0534

A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking

This paper investigates non-myopic path planning of mobile sensors for multi-target tracking. Such problem has posed a high computational complexity issue and/or the necessity of high-level decision making. Existing works tackle these issues by heuristically assigning targets to each sensing agent and solving the split problem for each agent. However, such heuristic methods reduce the target estimation performance in the absence of considering the changes of target state estimation along time. In this work, we detour the task-assignment problem by reformulating the general non-myopic planning problem to a distributed optimization problem with respect to targets. By combining alternating direction method of multipliers (ADMM) and local trajectory optimization method, we solve the problem and induce consensus (i.e., high-level decisions) automatically among the targets. In addition, we propose a modified receding-horizon control (RHC) scheme and edge-cutting method for efficient real-time operation. The proposed algorithm is validated through simulations in various scenarios.Comment: Copyright 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Effects of 1-MCP on Quality and Storability of Cherry Tomato (Solanum lycopersicum L.)

Cherry tomato is a perishable fruit due to its high rate of ethylene production and respiration during ripening. 1-Methylcyclopropene (1-MCP) is known to control ripening and reduce decay of fruit by inhibiting ethylene action. In the present study, the influence of 1-MCP application on quality and storability of ‘Unicorn’ cherry tomato was observed. Fruit at pink and red maturity stages were put in the commercial plastic containers and sealed with 40 μm low density polyethylene (LDPE) film, treated with 1-MCP (0 µL L−1 (control), 0.035 µL L−1 and 0.1 µL L−1), and stored at 10 °C in 85 ± 5% relative humidity (RH). The results indicated that application of 1-MCP at 0.1 µL L−1 significantly affected firmness, cell wall thickness, water soluble pectin, weight loss, surface color, lycopene content and physiological parameters in both pink and red maturity stages compared to 0.035 µL L−1 and control. 1-MCP treatment at 0.1 µL L−1 kept the fruits firmer than 0.035 µL L−1 and the control throughout the storage period for both maturity stages. Cell wall degradation in the control treatment was higher compared to the 0.1 µL L−1 1-MCP treated fruits in both maturity stages throughout the storage period. Results of this study revealed the effectiveness of application of 0.1 µL L−1 1-MCP on quality and shelf life of cherry tomato

Transparent conducting film fabricated by metal mesh method with Ag and cu@ag mixture nanoparticle pastes

Transparent conducting electrode film is highly desirable for application in touch screen panels (TSPs), flexible and wearable displays, sensors, and actuators. A sputtered film of indium tin oxide (ITO) shows high transmittance (90%) at low sheet resistance (50 ??/cm2). However, ITO films lack mechanical flexibility, especially under bending stress, and have limitation in application to large-area TSPs (over 15 inches) due to the trade-off in high transmittance and low sheet resistance properties. One promising solution is to use metal mesh-type transparent conducting film, especially for touch panel application. In this work, we investigated such inter-related issues as UV imprinting process to make a trench layer pattern, the synthesis of core-shell-type Ag and Cu@Ag composite nanoparticles and their paste formulation, the filling of Ag and Cu@Ag mixture nanoparticle paste to the trench layer, and touch panel fabrication processes