11 accepted papers
The deterioration phenomenon is common and lasting as machines' service time increases within energy-intensive manufacturing processes such as heat treatment, which may bring about processes time extension or even the breakdown of a machine. It is crucial to collaboratively optimize batch scheduling
Dynamic scheduling is one of the most important problems in the field of production scheduling. Existing ways to solve the problem are mainly based on experienced workers or automatic scheduling models (SMs). Because of the complementary advantages of workers and SMs, their combination has the poten
Achieving sustainability is currently an important development direction for the manufacturing industry. With the consideration of all pillars of sustainability, valid evaluation of sustainability during scheduling optimization has become an emerging critical issue in the production scheduling loops
As the focus on highly intelligent robots continues, a problem that cannot be ignored has emerged: resource con-straints. Considering the game problem of resource limitation and the level of intelligence, we focus on lightweight intelligence. This work is a further refinement of our previous work, a…
Feature extraction plays an important role in visual localization. Unreliable features on dynamic objects or repetitive regions will interfere with feature matching and challenge indoor localization greatly. To address the problem, we propose a novel network, RaP-Net, to simultaneously predict regio…
Service robots should be able to operate autonomously in dynamic and daily changing environments over an extended period of time. While Simultaneous Localization And Mapping (SLAM) is one of the most fundamental problems for robotic autonomy, most existing SLAM works are evaluated with data sequence…
A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for robot autonomy. For visual SLAM algorithms, though the theoretical framework has been well established for most aspects, feature extraction and association is still empirically designed in most cases, and can…
Limited energy supply and uncertain equipment state increase the complexity of production process. Peak power and maintenance-based demand response facilitates factories to adjust scheduling strategies to actual production circumstances, so that a rise in energy cost penalty and machine breakdown co
The recent breakthroughs in computer vision have benefited from the availability of large representative datasets (e.g. ImageNet and COCO) for training. Yet, robotic vision poses unique challenges for applying visual algorithms developed from these standard computer vision datasets due to their impl…
Approximate computing has drawn considerable attention to both academia and industry in the area of DNN hardware. Despite substantial efforts to design approximate circuits and building blocks, the resilience of DNN layers and structures remains an untapped field to explore. This paper presents an e…
A precision-improved processing architecture of physical computing for energy-efficient SIFT feature extraction algorithm has been proposed in this paper. With the novel physical computing technology of active resistor network (PC: ARN), the SIFT algorithm could be processed in analog signal domain…