The Analysis of design and manufacturing tasks using haptic and immersive VR - Some case studies

The use of virtual reality in interactive design and manufacture has been researched extensively but the practical application of this technology in industry is still very much in its infancy. This is surprising as one would have expected that, after some 30 years of research commercial applications of interactive design or manufacturing planning and analysis would be widespread throughout the product design domain. One of the major but less well known advantages of VR technology is that logging the user gives a great deal of rich data which can be used to automatically generate designs or manufacturing instructions, analyse design and manufacturing tasks, map engineering processes and, tentatively, acquire expert knowledge. The authors feel that the benefits of VR in these areas have not been fully disseminated to the wider industrial community and - with the advent of cheaper PC-based VR solutions - perhaps a wider appreciation of the capabilities of this type of technology may encourage companies to adopt VR solutions for some of their product design processes. With this in mind, this paper will describe in detail applications of haptics in assembly demonstrating how user task logging can lead to the analysis of design and manufacturing tasks at a level of detail not previously possible as well as giving usable engineering outputs. The haptic 3D VR study involves the use of a Phantom and 3D system to analyse and compare this technology against real-world user performance. This work demonstrates that the detailed logging of tasks in a virtual environment gives considerable potential for understanding how virtual tasks can be mapped onto their real world equivalent as well as showing how haptic process plans can be generated in a similar manner to the conduit design and assembly planning HMD VR tool reported in PART A. The paper concludes with a view as to how the authors feel that the use of VR systems in product design and manufacturing should evolve in order to enable the industrial adoption of this technology in the future

Fast, reliable and efficient database search motion planner (FREDS-MP) for repetitive manipulator tasks

University of Technology Sydney. Faculty of Engineering and Information Technology.This thesis presents FREDS-MP, a motion planning framework that leverages state of the art methods for solving a set of practical agricultural manipulator applications. Current methods exhibit unacceptably slow planning and execution times, hence FREDS-MP aims to bridge this gap by speeding up planning times whilst maintaining high reliability and solution efficiency. While only a specific set of applications are explored, FREDS-MP can be adopted for other similar applications seamlessly due to its general interface. FREDS-MP consists of three planning phases: offline, task and online. The offline planner pre-computes trajectories and cost information based on special cases that anticipate the real world. This pre-computed information is used by the task planner to compute accurate heuristics for sequencing tasks. The pre-computed trajectories are used as initial seeds by the online planner which utilises state of the art trajectory optimisers to adapt them in real-time to online tasks. Software simulations are performed to validate FREDS-MP and compare it to other state of the art planners. Further, the suitability of two commercial manipulators, six-DOF and seven-DOF, are compared for the intended applications. Several unconstrained and constrained tasks, commonly seen in agricultural applications, are tested under diverse obstacle configurations. Statistical results based on planner performance metrics are presented. From these results it was found that FREDS-MP significantly outperformed other state of the art planners when using a seven-DOF manipulator. Hence, an active perception experiment was carried out on a real Rethink Robotics Sawyer robot arm which was tasked to seek out apples on an artificial trellis and inspect them individually. The results from these experiments are presented and validate the practicality of FREDS-MP

The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions

Recent progress in Large Language Models (LLMs) has produced models that exhibit remarkable performance across a variety of NLP tasks. However, it remains unclear whether the existing focus of NLP research accurately captures the genuine requirements of human users. This paper provides a comprehensive analysis of the divergence between current NLP research and the needs of real-world NLP applications via a large-scale collection of user-GPT conversations. We analyze a large-scale collection of real user queries to GPT. We compare these queries against existing NLP benchmark tasks and identify a significant gap between the tasks that users frequently request from LLMs and the tasks that are commonly studied in academic research. For example, we find that tasks such as ``design'' and ``planning'' are prevalent in user interactions but are largely neglected or different from traditional NLP benchmarks. We investigate these overlooked tasks, dissect the practical challenges they pose, and provide insights toward a roadmap to make LLMs better aligned with user needs.Comment: EMNLP 202

Simple Algorithm for Simple Timed Games

version 1.1We propose a subclass of timed game automata (TGA), called Task TGA, representing networks of communicating tasks where the system can choose when to start the task and the environment can choose the duration of the task. We search to solve finite-horizon reachability games on Task TGA by building strategies in the form of Simple Temporal Networks with Uncertainty (STNU). Such strategies have the advantage of being very succinct due to the partial order reduction of independent tasks. We show that the existence of such strategies is an NP-complete problem. A practical consequence of this result is a fully forward algorithm for building STNU strategies. Potential applications of this work are planning and scheduling under temporal uncertainty