Hyperbolic sections in surface bundles

AbstractWe give conditions assuring that the given section in a surface bundle over the circle is hyperbolic in terms of the ‘‘projection" in the fiber surface according to the Nielsen–Thurston types of the monodromies

AI-Based Approach for Lawn Length Estimation in Robotic Lawn Mowers

This chapter describes a part of autonomous driving of work vehicles. This type of autonomous driving consists of work sensing and mobility control. Particularly, this chapter focuses on autonomous work sensing and mobility control of a commercial electric robotic lawn mower, and proposes an AI-based approach for work vehicles such as a robotic lawn mower. These two functions, work sensing and mobililty control, have a close correlation. In terms of efficiency, the traveling speed of a lawn mower, for example, should be reduced when the workload is high, and vice versa. At the same time, it is important to conserve the battery that is used for both work execution and mobility. Based on these requirements, this chapter is focused on developing an estimation system for estimating lawn grass lengths or ground conditions in a robotic lawn mower. To this end, two AI algorithms, namely, random forest (RF) and shallow neural network (SNN), are developed and evaluated on observation data obtained by a fusion of ten types of sensor data. The RF algorithm evaluated on data from the fusion of sensors achieved 92.3% correct estimation ratio in several experiments on real-world lawn grass areas, while the SNN achieved 95.0%. Furthermore, the accuracy of the SNN is 94.0% in experiments where sensor data are continuously obtained while the robotic lawn mower is operating. Presently, the proposed estimation system is being developed by integrating two motor control systems into a robotic lawn mower, one for lawn grass cutting and the other for the robot’s mobility

A Deep Learning-Enhanced Stereo Matching Method and Its Application to Bin Picking Problems Involving Tiny Cubic Workpieces

This paper proposes a stereo matching method enhanced by object detection and instance segmentation results obtained through the use of a deep convolutional neural network. Then, this method is applied to generate a picking plan to solve bin picking problems, that is, to automatically pick up objects with random poses in a stack using a robotic arm. The system configuration and bin picking process flow are suggested using the proposed method, and it is applied to bin picking problems, especially those involving tiny cubic workpieces. The picking plan is generated by applying the Harris corner detection algorithm to the point cloud in the generated three-dimensional map. In the experiments, two kinds of stacks consisting of cubic workpieces with an edge length of 10 mm or 5 mm are tested for bin picking. In the first bin picking problem, all workpieces are successfully picked up, whereas in the second, the depths of the workpieces are obtained, but the instance segmentation process is not completed. In future work, not only cubic workpieces but also other arbitrarily shaped workpieces should be recognized in various types of bin picking problems

Analysis of Some Lockout Avoidance Algorithms for the k-Exclusion Problem

We analyze two algorithms for the k-exclusion problem on the asynchronous multi-writer/reader shared memory model and show their correctness. The first algorithm is a natural extension of the n-process algorithm by Peterson for the mutual exclusion algorithm to the k-exclusion problem, and the second algorithm is a combination of the first algorithm and the tournament algorithm by Peterson and Fischer for the mutual exclusion problem. These two algorithms satisfy k-exclusion, and can tolerate up to k-1 process failures of the stopping type. The running times by the first algorithm and by the second algorithm are bounded by (n-k)c+O(n(n-k)2)l and (n/k)kc+O((n/k)k+1k)l, respectively, even if there exist at most k-1 process failures of the stopping type, where n is the number of processes, l is an upper bound on the time between successive two atomic steps for any faultless process, and c is an upper bound on the time that any user spends in the critical region

空間分布系の有限差分解法のための多段ダイアコプティックスの並列スケジューリングと計算・通信の複雑度

学位記番号:工博甲1