Learning from users for radical innovation

In today's environment of rapid technological change companies can not rely on incremental innovations alone. To sustain long-term competitiveness companies need to develop radical innovations as well. Such innovations typically incorporate new and highly complex technologies, create new markets or shift existing market structures, and require user learning as they often induce significant behaviour changes on side of the users. To systematically develop radical innovations firms need to involve the proper actors. One such important external actor in the development process of new products is the user. Our study focuses on the question what kind of users are able to actively contribute to the development of radical innovations and what firms can learn from them to improve their innovative capability. A multiple case study analysis was conducted in the field of medical technology. Five radical innovation projects were selected including medical robots and computer-assisted navigation systems. The case study analysis reveals that users with a unique set of characteristics can contribute substantially to the development of radical innovations. These users have a high motivation toward new solutions, are open to new technologies, possess diverse competencies, and are embedded into a very supportive context. Manufacturers that took over the ideas and prototypes of the inventive users benefited significantly. By learning from these users, firms were able to significantly improve their radical innovative capability. The paper contributes to technology and innovation management research in two ways. First, by exploring critical user characteristics for distinct phases of the radical innovation process, we provide first insights how manufacturing firms can more effectively identify and leverage valuable users for their radical innovation work. Thereby, we highlight the involvement of capable users as an effective learning mechanism to improve the radical innovation capability of a firm. Second, new perspectives on lead user research are provided by enriching the lead user concept with other crucial characteristics of innovative users. --Produktinnovation,Produktentwicklung,Benutzer / Beteiligung

A Simulation-Based Study of Maze-Solving-Robot Navigation for Educational Purposes

The point of education in the early stage of studying robotics is understanding its basic principles joyfully. Therefore, this paper creates a simulation program of indoor navigations using an open-source code in Python to make navigation and control algorithms easier and more attractive to understand and develop. We propose the maze-solving-robot simulation as a teaching medium in class to help students imagine and connect the robot theory to its actual movement. The simulation code is built for free to learn, improve, and extend in robotics courses or assignments. A maze-solving robot study case is then done as an example of implementing navigation algorithms. Five algorithms are compared, such as Random Mouse, Wall Follower, Pledge, Tremaux, and Dead-End Filling. Each algorithm is simulated a hundred times in every type of the proposed mazes, namely mazes with dead ends, loops only, and both dead ends and loops. The observed indicators of the algorithms are the success rate of the robots reaching the finish lines and the number of steps taken. The simulation results show that each algorithm has different characteristics that should be considered before being chosen. The recommendation of when-to-use the algorithms is discussed in this paper as an example of the output simulation analysis for studying robotics

Using Formal Methods for Autonomous Systems: Five Recipes for Formal Verification

Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into everyday settings. Autonomous systems need robust development and verification methods, but formal methods practitioners are often asked: Why use Formal Methods for Autonomous Systems? To answer this question, this position paper describes five recipes for formally verifying aspects of an autonomous system, collected from the literature. The recipes are examples of how Formal Methods can be an effective tool for the development and verification of autonomous systems. During design, they enable unambiguous description of requirements; in development, formal specifications can be verified against requirements; software components may be synthesised from verified specifications; and behaviour can be monitored at runtime and compared to its original specification. Modern Formal Methods often include highly automated tool support, which enables exhaustive checking of a system's state space. This paper argues that Formal Methods are a powerful tool for the repertoire of development techniques for safe autonomous systems, alongside other robust software engineering techniques.Comment: Accepted at Journal of Risk and Reliabilit

A novel algorithm for integrated control model using swarm robots for intruder detection and rescue schedules

Due to the development of computer controlled tools and expansion of integrated computing applications, more and more controller functions are turning to software implementations. A novel controlling algorithm is designed for continuous optimization tasks. However, they are used to thoroughly optimize and apply different areas. The most intelligent swarm algorithms have been designed for continuous optimization problems. However, they have been applied to discreet optimization and applications in different areas. This article gives experimental results on the control of swarm robots with the help of integrated control model (ICM), around its own axis. Such methodology is quite impressive in development of applications for surveillance, path planning, intruder and obstacle detection, model errors in communication to remove uncertainty. The ICM control design performance is based on comprehensive swarm robot model for the identification of actuators from testing data. The same ICM controllers are designed to be compared with the PID controllers in a variety of tests and collected feedback found 12.37%, 8.69% and 12.09% improved on the basis of thrust produced in the propellers for surveillance

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

On Determinism of Game Engines used for Simulation-based Autonomous Vehicle Verification

Game engines are increasingly used as simulation platforms by the autonomous vehicle (AV) community to develop vehicle control systems and test environments. A key requirement for simulation-based development and verification is determinism, since a deterministic process will always produce the same output given the same initial conditions and event history. Thus, in a deterministic simulation environment, tests are rendered repeatable and yield simulation results that are trustworthy and straightforward to debug. However, game engines are seldom deterministic. This paper reviews and identifies the potential causes of non-deterministic behaviours in game engines. A case study using CARLA, an open-source autonomous driving simulation environment powered by Unreal Engine, is presented to highlight its inherent shortcomings in providing sufficient precision in experimental results. Different configurations and utilisations of the software and hardware are explored to determine an operational domain where the simulation precision is sufficiently low i.e.\ variance between repeated executions becomes negligible for development and testing work. Finally, a method of a general nature is proposed, that can be used to find the domains of permissible variance in game engine simulations for any given system configuration.Comment: 17 pages, 9 figures, 1 tabl

Swarm robotics: Cooperative navigation in unknown environments

Swarm Robotics is garnering attention in the robotics field due to its substantial benefits. It has been proven to outperform most other robotic approaches in many applications such as military, space exploration and disaster search and rescue missions. It is inspired by the behavior of swarms of social insects such as ants and bees. It consists of a number of robots with limited capabilities and restricted local sensing. When deployed, individual robots behave according to local sensing until the emergence of a global behavior where they, as a swarm, can accomplish missions individuals cannot. In this research, we propose a novel exploration and navigation method based on a combination of Probabilistic Finite Sate Machine (PFSM), Robotic Darwinian Particle Swarm Optimization (RDPSO) and Depth First Search (DFS). We use V-REP Simulator to test our approach. We are also implementing our own cost effective swarm robot platform, AntBOT, as a proof of concept for future experimentation. We prove that our proposed method will yield excellent navigation solution in optimal time when compared to methods using either PFSM only or RDPSO only. In fact, our method is proved to produce 40% more success rate along with an exploration speed of 1.4x other methods. After exploration, robots can navigate the environment forming a Mobile Ad-hoc Network (MANET) and using the graph of robots as network nodes