Recognising and tracking human actions from videos is crucial for human-robot collaborative assembly (HRCA). However, traditional action segmentation methods suffer from limited scene adaptability, partly because they conceptualise actions as unified verb-object entities with complete semantics. To overcome this, we propose a compositional action segmentation method. Following the human-robot shared assembly taxonomy, we deconstruct an assembly action into four elements: action verb, manipulated object, target object and tool. Our approach employs individual segmentation models for each action element, and then integrates general knowledge from large language models and domain-specific knowledge from predefined rules to form semantic-complete actions. Our method’s emphasis on general action elements and a modular design endows it with greater flexibility and adaptability than traditional approaches. Another attribute of our method is its capability to segment actions of each hand concurrently, facilitating more nuanced HRCA. Comparative experiments validate the superiority of our method over traditional action segmentation methods. More details can be found at https://github.com/LISMS-AKL-NZ/DuCAS.

Cloud manufacturing is a novel service-oriented networked manufacturing paradigm that aims to provide on-demand manufacturing cloud services to consumers. Scheduling is a critical means for achieving that aim. Currently, research on scheduling in cloud manufacturing is still in its infancy, and current frequently adopted meta-heuristic algorithm-based approaches have some shortcomings, e.g. they require complex design processes and lack adaptability to dynamic environments. Deep reinforcement learning (DRL) that combines advantages of reinforcement learning and deep learning provides an efficient, adaptive and intelligent approach for solving scheduling problems in cloud manufacturing. However, to the best of our knowledge, there has been no application of DRL to scheduling in cloud manufacturing. This work conducts a preliminary exploration over this issue. First, a DRL-based framework for scheduling in cloud manufacturing is proposed. Then a DRL model for online single-task scheduling in cloud manufacturing is presented to demonstrate the effectiveness of the framework. DRL as a promising technique will find wide applications in cloud manufacturing, and this work can provide some reference for future research on this.

This paper introduces a generic framework for field surveillance using consumer rotorcrafts and ground vehicles. Building such an autonomous system comes with two key challenges in persistent perception and obstacle avoidance. We begin with explaining two core algorithms to solve the challenges: an auto-landing algorithm that enables a quadrotor to land on a moving ground vehicle at a speed of 6.00 m/s, and an obstacle avoidance algorithm that ensures the safety of the quadrotor during searching process. On the basis of these algorithms, the architecture and infrastructure of Hawkeye framework are presented as well. Hawkeye is designed to be a generic platform with extensibility that allows integration of other domain applications. We demonstrate the potential of Hawkeye framework in a simulated agriculture monitoring mission and report its performance at the end of the paper.

In a conventional CNC system, communications between the motion controller and the analogue servo driver usually take place in a unidirectional manner, i.e., from the controller to the driver. In order to increase the interoperability level between the motion controller and the driver, Fieldbus is used in this research. The digital servo in a Fieldbus-based system enables applications with all servo loops closed. Functions that have been traditionally executed by the motion controller can now be shifted to the driver. In this research, the traditional CNC system has been redesigned based on the component technology. Following the analysis of the architecture of a traditional CNC and the features of a Fieldbus, component models have been developed for the motion controller and the driver. This Fieldbus-based CNC system gives the much-needed interoperability between the motion controller and the driver. A comparative experiment based on a four-axis CNC system has been carried out to showcase the component model-based system.

Interoperable manufacturing systems help manufacturing companies stay competitive in the environment of frequent and unpredictable market changes. An important part of a manufacturing system is computer numerically controlled (CNC) machine tools. Over the years, G-codes have been extensively used by CNC machine tools and are now considered as a bottleneck for making these machines adaptable and interoperable. Two new technologies emerged in recent years: Standard for the Exchange of Product data for Numerical Control (STEP-NC) and function blocks. The STEP-NC data model represents a common standard for NC programming, making the goal of a generic NC code generation facility a reality. Function blocks are an emerging IEC standard for distributed industrial processes and control systems. They can be used for CNC controls to encapsulate machining data, such as machining features and their needed algorithms. This paper introduces the above two new standards and the technologies that are developed based on the standards. The main body is devoted to analyze the standards from the functionality viewpoint. These functionalities include, bidirectional information flow in computer-aided design/computer-aided manufacturing, data sharing over the Internet, the use of feature-based machining concept, modularity and reusability, intelligent and autonomous CNC, and portability among resources. Some implementations are also presented to showcase how the standards are used to develop technologies for interoperable machining. Note to Practitioners-Modern computer numerically controlled (CNC) machine tools are limited in functions because their controllers rely on G-codes for communications. G-code is considered a "dumb" language as it only documents instructional and procedural data, leaving most of the design information behind. G-code programs are also hardware dependent, denying modern CNC machine tools desired interoperability and portability. In recent years, two new standards emerged, STEP-NC and function blocks. They may hold the key to empowering CNC machine tools with richer information which, in turn, gives CNC machine tools the ability to "think" intelligently and to be interoperable. This paper introduces these two standards, the technologies that have been developed based on the standards and some prototype systems using the standards and technologies. The intention is not to highlight any achieved research outcome. Instead, the focus is on informing the research and practical world about these new standards, analyzing them from the viewpoint of supporting interoperable CNC machine tools, and offering some futuristic views about these standards and technologies. While these standards are still in their infancy, research activities and prototype systems are already coming thick and fast. There seems to be a "healthy" mixture of participants working in the field. They range from the manufacturers of all systems related to the data interface (i.e., CAM systems, controls, and machine tools), to the users and academic institutions.