Narrow Results

With the development of the Internet of Things and devices continuing to scale, using cloud computing resources to process data in real-time is challenging. Edge computing technologies can improve real-time performance in processing data. By introducing the FPGA into the computing node and using the dynamic reconfigurability of the FPGA, the FPGA-based edge node can increase the edge node capability. In this paper, a task-based collaborative method for an FPGA-based edge computing system is proposed in order to meet the collaboration among FPGA-based edge nodes, edge nodes, and the cloud. The modeling of the task includes two parts, task information and task-dependent file. Task information is used to describe the running information and dependency information required for the task execution. Task-dependent file contains the configuration bit-stream of FPGA in running of the task. By analyzing the task behavior, this paper builds four basic behaviors, analyzes the critical attributes of each behavior, and summarizes the task model suitable for FPGA-based edge nodes. Tasks with specific functions can be created by modifying different attributes of model nodes. Finally, the availability of the model and the task-based collaborative method are verified by simulation experiments. The experimental results that the task model proposed in this paper can meet cloud-edge collaboration in the FPGA-based edge computing environment.

The research on medical robotics is starting to address the autonomous execution of surgical tasks, without effective intervention of humans apart from supervision and task configuration. This paper addresses the complete automation of a surgical robot by combining advanced sensing, cognition and control capabilities, developed according to rigorous assessment of surgical requirements, formal specification of robotic system behavior and software design and implementation based on solid tools and frameworks. In particular, the paper focuses on the cognitive control architecture and its development process, based on formal modeling and verification methods as best practices to ensure safe and reliable behavior. Full implementation of the proposed architecture has been tested on an experimental setup including a novel robot specifically designed for surgical applications, but adaptable to different selected tasks (i.e. needle insertion, wound suturing).