This paper presents a new solution approach for managing the motion of a fleet of autonomous vehicles (AVs) in indoor factory environments. AVs are requested to serve a number of workstations (WS) (following a specified desired production plan for materials requirements) while taking into account the safe movement (collisions avoidance) in the shop floor as well as time duration and energy resources. The proposed approach is based on the Bump-Surface concept to represent the 2D environment through a single mathematical entity. The solution of the combined problem of path planning and task scheduling is searched on a higher-dimension B-surface (in our case 3D) in such a way that its inverse image into the robot environment satisfies the given objectives and constraints. Then, a modified Genetic Algorithm (GA) is used to search for a near-optimum solution. The objective of the fleet coordination consists of determining the best feasible paths for the AVs so that all the WS are served at the lowest possible cost. The efficiency of the developed method is investigated and discussed through characteristic simulated experiments concerning a variety of operating environments.

In this paper, the forward kinematic analysis of 3-degree-of-freedom planar parallel robots with identical limb structures is presented. The proposed algorithm is based on Study's kinematic mapping (E. Study, “von den Bewegungen und Umlegungen,” Math. Ann.39, 441–565 (1891)), resultant method, and the Gröbner basis in seven-dimensional kinematic space. The obtained solution in seven-dimensional kinematic space of the forward kinematic problem is mapped into three-dimensional Euclidean space. An alternative solution of the forward kinematic problem is obtained using resultant method in three-dimensional Euclidean space, and the result is compared with the obtained mapping result from seven-dimensional kinematic space. Both approaches lead to the same maximum number of solutions: 2, 6, 6, 6, 2, 2, 2, 6, 2, and 2 for the forward kinematic problem of planar parallel robots; 3-RPR, 3-RPR, 3-RRR, 3-RRR, 3-RRP, 3-RPP, 3-RPP, 3-PRR, 3-PRR, and 3-PRP, respectively.

One mode of creative design is for designers to draw analogies that connect the design domain (e.g., a mechanical device) to some other domain from which inspiration is drawn (e.g., a biological system). The identification and application of analogies can be supported by software tools that store, structure, present, or propose source domain stimuli from which such analogies might be constructed. For these tools to be effective and not impact the design process in negative ways, they must fit well with the information and interaction needs of their users. However, the user requirements for these tools are seldom explicitly discussed. Furthermore, the literature that supports the identification of such requirements is distributed across a number of different domains, including those that address analogical design (especially biomimetics), creativity support tools, and human–computer interaction. The requirements that these literatures propose can be divided into those that relate to the information content that the tools provide (e.g., level of abstraction or mode of representation) and those that relate to the interaction qualities that the tools support (e.g., accessibility or shareability). Examining the relationships between these requirements suggests that tool developers should focus on satisfying the key requirements of open-endedness and accessibility while managing the conflicts between the other requirements. Attention to these requirements and the relationships between them promises to yield analogical design support tools that better permit designers to identify and apply source information in their creative work.

Internal analogies are created if the knowledge of source domain is obtained only from the cognition of designers. In this paper, an understanding of the use of internal analogies in conceptual design is developed by studying: the types of internal analogies; the roles of internal analogies; the influence of design problems on the creation of internal analogies; the role of experience of designers on the use of internal analogies; the levels of abstraction at which internal analogies are searched in target domain, identified in source domain, and realized in the target domain; and the effect of internal analogies from the natural and artificial domains on the solution space created using these analogies. To facilitate this understanding, empirical studies of design sessions from earlier research, each involving a designer solving a design problem by identifying requirements and developing conceptual solutions, without using any support, are used. The following are the important findings: designers use analogies from the natural and artificial domains; analogies are used for generating requirements and solutions; the nature of the design problem influences the use of analogies; the role of experience of designers on the use of analogies is not clearly ascertained; analogical transfer is observed only at few levels of abstraction while many levels remain unexplored; and analogies from the natural domain seem to have more positive influence than the artificial domain on the number of ideas and variety of idea space.

This paper presents a framework for the interactions between the processes of mapping and rerepresentation within analogy making. Analogical reasoning systems for use in design tasks require representations that are open to being reinterpreted. The framework, interpretation-driven mapping, casts the process of constructing an analogical relationship as requiring iterative, parallel interactions between mapping and interpreting. This paper argues that this interpretation-driven approach focuses research on a fundamental problem in analogy making: how do the representations that make new mappings possible emerge during the mapping process? The framework is useful for both describing existing analogy-making models and designing future ones. The paper presents a computational model informed by the framework Idiom, which learns ways to reinterpret the representations of objects as it maps between them. The results of an implementation in the domain of visual analogy are presented to demonstrate its feasibility. Analogies constructed by the system are presented as examples. The interpretation-driven mapping framework is then used to compare representational change in Idiom to that in three previously published systems.

We aim to examine the potential of using analogies in design education and to compare the roles of analogies in explaining versus inspiring in engineering design. We review existing research in analogical thinking, with a focus on scientific discourse and education. Then we explore the role of analogies in design education in making concepts more relatable by asking six participants in a graduate-level design course to generate analogies for course topics. We describe criteria developed to evaluate the analogies and present these evaluations. We then asked participants to perform divergent thinking tests, but we found no significant correlation between these and analogy scores. The participants were also asked to reflect on what constitutes an effective analog, describe their process of identifying analogies, and provide their definitions of analogies. We describe possible links between these comments and the ratings of their analogies. We then draw on results in using analogies in pedagogy to inform and reflect on obstacles we encountered in the use of analogies to inspire. Specifically, we related them to our experience with biomimetic or biologically inspired design, where we used a natural-language search approach to identify relevant analogies. Three aspects discussed are familiarity of source analogies, boundaries of parallels between source analogies and target concepts, and concreteness of source analogies. Finally, we discuss possible pedagogical benefits of eliciting analogies on course topics from students, namely, using the elicited analogies as tools for improved student engagement as well as more prompt instructor feedback.

The concept of stochastic precedence between two real-valued random variables has often emerged in different applied frameworks. In this paper, we analyze several aspects of a more general, and completely natural, concept of stochastic precedence that also had appeared in the literature. In particular, we study the relations with the notions of stochastic ordering. Such a study leads us to introducing some special classes of bivariate copulas. Motivations for our study can arise from different fields. In particular, we consider the frame of Target-Based Approach in decisions under risk. This approach has been mainly developed under the assumption of stochastic independence between “Prospects” and “Targets”. Our analysis concerns the case of stochastic dependence.

The aim of this study was to gain further insight into how analogical reasoning and mental simulation, two cognitive strategies, influence team dynamics in innovative product design. A particular emphasis was placed on exploring the association between these two strategies and team cohesion and team collaboration. Analogies were coded for “analogical distance” (i.e., within domain or between domain) and “analogical purpose” (i.e., problem identification, function finding, solution generation, and explanation). The results indicated that the presence of either analogizing or mental simulation was related to team cohesion and team collaboration, with mental simulation having an especially marked association with team collaboration. Within-domain analogizing was found to enhance team collaboration, but it did not influence team cohesion. Furthermore, all types of analogical purpose showed a similar association with team cohesion, whereas solution generation and function finding had a stronger association with team collaboration. We propose that analogizing and mental simulations are strategies that serve valuable functions in engendering enhanced cohesion and collaboration, which might be expected to lead to more effective design outcomes, although this remains an empirical question in need of further corroboration.

Digital libraries of case studies of analogical design have been popular since their advent in the early 1990s. We consider four benefits of digital libraries of case studies of analogical design in the context of biologically inspired design. First, a digital library affords documentation. The 83 case studies in our work come from 8 years of extended, collaborative design projects in an interdisciplinary class on biologically inspired design. Second, a digital library provides on-demand access to the case studies. We describe a web-based library of case studies of biologically inspired design called the Design Study Library (DSL). Third, a compilation of case studies supports analyses of broader patterns and trends. As an example, an analysis of DSL's case studies found that environmental sustainability was a major factor in about a third of the case studies and an explicit design goal in about a fourth. Fourth, a digital library of case studies can support analogical learning. Preliminary results from an exploratory study indicate that DSL may support novice learning about the processes of biologically inspired design.

Many tools are being developed to assist designers in retrieving analogies. One critical question these designers face is how these analogues should be represented in order to minimize design fixation and maximize idea generation. To address this question, an experiment is presented that compares various representations' influence on creativity and design fixation. This experiment presents an effective example (analogue) as computer-aided design (CAD), sketch, or photograph representations. We found that all representations induced fixation, and the degree of fixation did not vary significantly. We also found that CAD representations encourage engineering designers to identify and copy the key effective features of the example. CAD and photo representations also produced a higher quality of design concepts. Results from this experiment offer insights into how these various representations may be used in examples during idea generation; CAD representations appear to offer the greatest advantages during the idea generation process. The results from this experiment also indicate that analogical databases of effective design examples should include CAD and photolike images of the analogue rather than sketches.

We examine how overflow policies in a multi-skill call center should be designed to accommodate performance measures that depend on waiting time percentiles such as service level. This is done using a discrete Markovian approximation of the waiting time of the first customers waiting in line. A Markov decision chain is used to determine the optimal policy. This policy outperforms considerably the ones used most often in practice, which use a fixed threshold. The present method can be used also for other call-center models and other situations where performance is based on actual waiting times and customers are treated in a FCFS order.

This paper presents a systematic method for dealing with mobility analysis and structural synthesis of a class of important spatial mechanisms with coupling chains, which involve more complex coupling relations than spatial parallel mechanisms. First, an approach to the establishment of the motion screw equation of the class of mechanisms is derived. Then, a general methodology for mobility analysis along with detection of rigid substructures is proposed based on the motion screw equation. Third, the principle of structural synthesis of the class of mechanisms is established on the basis of the method of mobility analysis. Finally, some novel spatial mechanisms with coupling chains are synthesized, illustrating the effectiveness of the method. The study of the paper will benefit structural analysis and synthesis of more complex spatial mechanisms with coupling chains.

This paper treats the systematic injury analysis of lower arm robot–human impacts. For this purpose, a passive mechanical lower arm (PMLA) was developed that mimics the human impact response and is suitable for systematic impact testing and prediction of mild contusions and lacerations. A mathematical model of the passive human lower arm is adopted to the control of the PMLA. Its biofidelity is verified by a number of comparative impact experiments with the PMLA and a human volunteer. The respective dynamic impact responses show very good consistency and support the fact that the developed device may serve as a human substitute in safety analysis for the described conditions. The collision tests were performed with two different robots: the DLR Lightweight Robot III (LWR-III) and the EPSON PS3L industrial robot. The data acquired in the PMLA impact experiments were used to encapsulate the results in a robot independent safety curve, taking into account robot's reflected inertia, velocity and impact geometry. Safety curves define the velocity boundaries on robot motions based on the instantaneous manipulator dynamics and possible human injury due to unforeseen impacts.

A new class of weighted generalized gamma distribution (WGGD) and related distributions are presented. Theoretical properties of the generalized gamma model, WGGD including the hazard function, reverse hazard function, moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis, and entropy measures are derived. The results presented here generalizes the generalized gamma distribution and includes several distributions as special cases. The special cases include generalized gamma, weighted gamma, weighted exponential, weighted Weibull, weighted Rayleigh distributions, and their underlying or parent distributions.