This paper argues that there is no shared understanding (i.e. an ontology) of the design activities that designers perform in the design process. Hence the purpose of the paper was directed towards identifying and classifying a generic set of design activities from published literature into what are referred to as design definition activities, design evaluation activities and design management activities. In an attempt to achieve a shared understanding of these activities, a set of consistent and coherent definitions of these activities are deliberated and presented. A knowledge level representation based on Newells Knowledge Level hypothesis governed by the Principle of Rationality is used to represent a design activity that is motivated by a design goal of that activity through which input knowledge is changed into output knowledge by the design agents knowledge. The ontological completeness, clarity and coherence of activities are evaluated through a protocol analysis and the design process in the domain of electronic design (in particular System-on-a-Chip designs (SoC))

The objective of this research is to apply the neural network approach to the dynamic job shop scheduling problem. A feed-forward back propagation neural network is designed and trained to recognize the individual contributions of traditional dispatch rules.The network is incorporated into an expert system which activates the network according to the prevailingshop environment. The effectivenessof the approach iscompared with the traditional dispatch rule approach as well as a composite ruleexpert system. Resultsof schedulingwith a neural network show that the network is able to perform well against its component factors for job lots with varying arrival rates.

Achieving human-robot cooperation in a telerobotics system is the focus of this paper. The implementation of human-robot systems can be extremely challenging when the robot is not directly controlled by the human. The interaction mode, depending on the task context, can be continuous manual, semi-autonomous or autonomous. To address the Human-Robot Interaction (HRI) issues in such a system, a concept of seamless HRI is introduced. Seamless HRI implies flexibility in human control in interacting with a robot in different situations, and the adaptability of the robot autonomy in response to the human control. The main idea is to design a telerobotics system that allows a shift from manual to autonomous operation, dynamically, via different human-robot roles and relationships. These roles are Master-Slave, Supervisor-Subordinate, Partner-Partner, Teacher-Learner and Full Autonomous mode by the robot. This paper presents the theoretical foundations and the requirements for seamless HRI. An implementation of the concept and an experimental evaluation is presented.

Learning in design is a phenomenon observed in design practice. Yet there is no comprehensive model or theory that explains the phenomenon and hence serves as a basis upon which a shared understanding can be evolved. This paper describes the development and evolution of a novel model of learning in design, LinD, which seeks to address the need for such a model. The model features formalisms for describing the cognitive activities of design and learning and three links that explain the interactions between these activities: the epistemic, teleological and temporal

This paper describes the design and implementation of a testbed for facilitating the study of human-robot interactions (HRI). HRI has long been a part of robotics research, where humans were typically required to guide the robot task in progress and to ensure safe operation. The current state of human interaction with robots, versus simple “machines” (e.g. in manufacturing automation) is quite different. This called for the need to look into different interaction roles between humans and robots. Robots differ from simple machines in that they are mobile, some may be autonomous and hence not as predictable in their actions. To facilitate the research in this domain, the aim is to develop an easy to use and safe front-end human-robot system for human users to interact with physical mobile robots. This testbed provides different types of system configurations (i.e. one human to one robot, one human to multiple robots, etc.) and interfaces for conducting experiments under different HRI scenarios.