DOCSLIB.ORG

Simulating Complex Robotic Scenarios with MORSE

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Simulating complex robotic scenarios with MORSE Gilberto Echeverria, Séverin Lemaignan, Arnaud Degroote, Simon Lacroix, Michael Karg, Pierrick Koch, Charles Lesire, Serge Stinckwich To cite this version: Gilberto Echeverria, Séverin Lemaignan, Arnaud Degroote, Simon Lacroix, Michael Karg, et al.. Simu- lating complex robotic scenarios with MORSE. 3rd International Conference on Simulation, Modeling, and Programming for Autonomous Robots, Nov 2012, Tsukuba, Japan. pp.197-208, 10.1007/978-3- 642-34327-8_20. hal-00988475 HAL Id: hal-00988475 https://hal.archives-ouvertes.fr/hal-00988475 Submitted on 8 May 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Simulating complex robotic scenarios with MORSE Gilberto Echeverria1⋆, S´everin Lemaignan1,2⋆⋆, Arnaud Degroote1⋆⋆⋆, Simon Lacroix1†, Michael Karg2‡, Pierrick Koch3§, Charles Lesire4¶, and Serge Stinckwich3,5k 1 CNRS, LAAS, 7 avenue du colonel Roche, F-31077 Toulouse, France / Universit´e de Toulouse, UPS, INSA, INP, ISAE, LAAS, F-31077 Toulouse, France 2 Institute for Advanced Studies, Technische Universit¨at M¨unchen, D-85748 Garching, Germany 3 UMR 6072 GREYC Universit´ede Caen-Basse Normandie/CNRS/ENSICAEN, France 4 ONERA – the French Aerospace Lab, F-31055, Toulouse, France 5 UMI 209 UMMISCO IRD/IFI/Vietnam National University, Vietnam Abstract. MORSE is a robotic simulation software developed by roboti- cists from several research laboratories. It is a framework to evaluate robotic algorithms and their integration in complex environments, mod- eled with the Blender 3D real-time engine which brings realistic rendering and physics simulation. The simulations can be specified at various levels of abstraction. This enables researchers to focus on their field of interest, that can range from processing low-level sensor data to the integration of a complete team of robots. After nearly three years of development, MORSE is a mature tool with a large collection of components, that pro- vides many innovative features: software-in-the-loop connectivity, multi- ple middleware support, configurable components, varying levels of simu- lation abstraction, distributed implementation for large scale multi-robot simulations and a human avatar that can interact with robots in virtual environments. This paper presents the current state of MORSE, high- lighting its unique features in use cases. 1 Introduction Simulations are an essential component in robotics research, allowing the eval- uation and validation of many sorts of developments before their integration ⋆ [email protected] ⋆⋆ [email protected] ⋆⋆⋆ [email protected] † [email protected] ‡ [email protected] § [email protected][email protected] k [email protected] on-board real robots. For such validations to be useful, the simulation must pro- vide enough fidelity with respect to the real world, within the requirements of the considered robotics application. Creating a fully realistic simulation in every aspect remains nearly impossible and sometimes can also be seen as an incon- venience. Therefore numerous simulators are focused on a given specific aspect (e.g. terramechanics to study locomotion, contact forces to study manipulation, realistic photo-rendering to study vision algorithms, ...). The MORSE simulator presented here is not targeted to the study of a spe- cific domain of robotics, but is rather meant as a tool that can be used to test and evaluate integrated robot software, i.e. the suite of processes required to au- tonomously achieve complex missions. Using Blender to simulate photo-realistic 3D worlds and the associated physics engine, it brings enough realism to eval- uate complete sets of software components within a wide range of application contexts. The simulator is designed to be useful under varied environments, and pro- vides features to adapt itself to existing robotic architectures, without imposing any changes on them to connect with MORSE. It has modular components that are versatile and configurable, to permit software-in-the-loop testing of robotics software. Input from several researchers has guided the evolution of this tool to satisfy the requirements of different labs, while keeping to its design principles. MORSE works on all major software platforms: win32, Linux and OS X. It is developed as an open–source project with a BSD 3-clause license. 6 The outline of this paper is as follows: Section 2 reviews other compara- ble robotics simulators, and Section 3 introduces the main design principles of MORSE. Section 4 is the heart part of the article: it depicts the main features of MORSE, each being exemplified with the projects for which they were developed. Finally Section 5 gives the conclusion and future plans for the simulator. 2 Related Work The Player/Stage/Gazebo[1] is a well known robotics suite. It is a full set of tools that include the Player communication layer and two integrated simula- tors: Stage [2] is basically a 2D simulator optimized for navigation on flat and closed environments. One of its advantages is the capability to handle very large numbers of simplified robots [3]. However, it is not ideal for more complex sce- narios, specially in 3D space. The more recent Gazebo [4] was developed to cover these shortcomings. It has received an important boost in its development with its integration into the ROS platform, and has thus become the most commonly used robotics simulator. It integrates very well with ROS and Player, but con- nectivity with other middlewares requires additional programming. The Unified System for Automation and Robot Simulation (USARSim)[5] shares many design concepts with MORSE. It was initially developed as a simu- 6 User documentation and additional information are available at http://morse. openrobots.org, and the source code can be downloaded from http://github. com/laas/morse.git. lator for search and rescue operations, uses the Unreal Engine gaming platform and is built with the concept of modular components. It is widely used as an evaluation tool for the well known RoboCup competitions. However, it uses an adhoc interface to communicate with external software and does not support some of the most common robotics middlewares. The Unreal Development Kit (UDK) used is a closed-source library and is not available on every platform. Webots [6] is a popular commercial simulator. It provides a full programming environment to create customized robots and environments, but the interface to construct new components and robots is unintuitive and complex, requiring searching trough data trees to adjust physical and geometrical parameters. It also has an integrated code editor, but the control programs created in it must later be converted and transferred to the final robot platform. Another commercial simulator is V-REP [7], with a large variety of com- ponents and sensors available. It allows scripting of the components using the LUA language. Being modular, it allows for copy-and-paste functionality of the components. However, it provides no native method for communication with middlewares; such functionality must be provided by the user in the form of add-ons. 3 MORSE Architecture Overview The Modular Open Robots Simulation Engine (MORSE) is a library of Python scripts that run on the Blender Game Engine (BGE) to interface a 3D virtual environment with external robotics software. Its main design principles have been described in [8], they are quickly recalled here. The BGE is used as the base platform for the graphical display of the sim- ulated world and the physics simulation, using the Bullet physics library. The simulation is organized as a main core of control functionality that initializes and coordinates the events in the BGE, and a collection of components that can be used to assemble a robot with sensors and actuators. A variety of communication tools allow each of the MORSE components to connect with external robotics software through middlewares. MORSE has support for some of the most com- monly used robotics middlewares nowadays, including ROS [9], Pocolibs [10] and YARP [11]. Other middlewares are regularly being added, mainly driven by the needs of new users. This process is simple, as existing middleware bindings can be used as templates for the new ones. MORSE sensors and actuators are minimalistic in their functionality and completely middleware agnostic. They can provide similar data as their real world counterparts, but some of them have multiple variants that can work at different levels of realism and abstraction. The data employed by the components can be altered through the use of components called modifiers. These add noise or change the data as required to better match the data with real sensors/actu- ators (for instance, transforming the coordinate frame used by Blender into the Universal Transverse Mercator coordinate system, or adding noise to images cap- tured by Blender cameras). When a simulation scene is created, the components are linked to middlewares as specified in a configuration script, and the neces- sary functionality is added to the components to be able to transmit/receive data through the middleware as data streams or synchronous/asynchronous requests. The whole data flow in MORSE can be seen in the diagram of Fig. 1. Fig. 1: Overview of the data flow in MORSE, between the simulated world in Blender and the external robotics software MORSE can be easily extended by adding new components that inherit from the existing base classes. All components are programmed in Python, since this is the language that Blender uses for its scripts. However, when coding components that require a faster processing time, they can be implemented in C/C++ and interfaced with Python using Swig.
Recommended publications
  • Annual Report 2014 OUR VISION

    Annual Report 2014 OUR VISION

    AMOS Centre for Autonomous Marine Operations and Systems Annual Report 2014 Annual Report OUR VISION To establish a world-leading research centre for autonomous marine operations and systems: To nourish a lively scientific heart in which fundamental knowledge is created through multidisciplinary theoretical, numerical, and experimental research within the knowledge fields of hydrodynamics, structural mechanics, guidance, navigation, and control. Cutting-edge inter-disciplinary research will provide the necessary bridge to realise high levels of autonomy for ships and ocean structures, unmanned vehicles, and marine operations and to address the challenges associated with greener and safer maritime transport, monitoring and surveillance of the coast and oceans, offshore renewable energy, and oil and gas exploration and production in deep waters and Arctic waters. Editors: Annika Bremvåg and Thor I. Fossen Copyright AMOS, NTNU, 2014 www.ntnu.edu/amos AMOS • Annual Report 2014 Table of Contents Our Vision ........................................................................................................................................................................ 2 Director’s Report: Licence to Create............................................................................................................................. 4 Organization, Collaborators, and Facts and Figures 2014 ......................................................................................... 6 Presentation of New Affiliated Scientists...................................................................................................................
  • An Introduction to the NASA Robotics Alliance Cadets Program

    An Introduction to the NASA Robotics Alliance Cadets Program

    Session F An Introduction to the NASA Robotics Alliance Cadets Program David R. Schneider, Clare van den Blink NASA, DAVANNE, & Cornell University / Cornell University CIT [email protected], [email protected] Abstract The 2006 report National Defense Education and Innovation Initiative highlighted this nation’s growing need to revitalize undergraduate STEM education. In response, NASA has partnered with the DAVANNE Corporation to create the NASA Robotics Alliance Cadets Program to develop innovative, highly integrated and interactive curriculum to redesign the first two years of Mechanical Engineering, Electrical Engineering and Computer Science. This paper introduces the NASA Cadets Program and provides insight into the skill areas targeted by the program as well as the assessment methodology for determining the program’s effectiveness. The paper also offers a brief discussion on the capabilities of the program’s robotic platform and a justification for its design into the program. As an example of the integration of the robotic platform with the program’s methodologies, this paper concludes by outlining one of the first educational experiments of NASA Cadets Program at Cornell University to be implemented in the Spring 2007 semester. I. Introduction To be an engineer is to be a designer, a creator of new technology, and the everyday hero that solves society’s problems through innovative methods and products by making ideas become a reality. However, the opportunity to truly explore these key concepts of being an engineer are often withheld from most incoming engineering students until at least their junior year causing many new students to lose motivation and potentially leave the program.
  • Modular Open Robots Simulation Engine: MORSE

    Modular Open Robots Simulation Engine: MORSE

    Modular Open Robots Simulation Engine: MORSE Gilberto Echeverria and Nicolas Lassabe and Arnaud Degroote and Severin´ Lemaignan Abstract— This paper presents MORSE, a new open–source robotics simulator. MORSE provides several features of interest to robotics projects: it relies on a component-based architecture to simulate sensors, actuators and robots; it is flexible, able to specify simulations at variable levels of abstraction according to the systems being tested; it is capable of representing a large variety of heterogeneous robots and full 3D environments (aerial, ground, maritime); and it is designed to allow simu- lations of multiple robots systems. MORSE uses a “Software- (a) A mobile robot in an indoor scene (b) A helicopter and two mobile in-the-Loop” philosophy, i.e. it gives the possibility to evaluate ground robots outdoors the algorithms embedded in the software architecture of the robot within which they are to be integrated. Still, MORSE Fig. 1: Screenshots of the MORSE simulator. is independent of any robot architecture or communication framework (middleware). MORSE is built on top of Blender, using its powerful features and extending its functionality through Python scripts. sensor or path planning for a particular kinematic system Simulations are executed on Blender’s Game Engine mode, [3], [4], [5]; such simulators are highly specialised (“Unitary which provides a realistic graphical display of the simulated Simulation”). On the other hand, some applications require environments and allows exploiting the reputed Bullet physics a more general simulator that can allow the evaluation of engine. This paper presents the conception principles of the simulator and some use–case illustrations.
  • The Chirps Prototyping System

    The Chirps Prototyping System

    Digital Commons @ George Fox University Faculty Publications - Department of Electrical Department of Electrical Engineering and Engineering and Computer Science Computer Science 2011 The hirC ps Prototyping System Gary Spivey George Fox University, [email protected] Follow this and additional works at: http://digitalcommons.georgefox.edu/eecs_fac Part of the Electrical and Computer Engineering Commons Recommended Citation Spivey, Gary, "The hirC ps Prototyping System" (2011). Faculty Publications - Department of Electrical Engineering and Computer Science. Paper 9. http://digitalcommons.georgefox.edu/eecs_fac/9 This Article is brought to you for free and open access by the Department of Electrical Engineering and Computer Science at Digital Commons @ George Fox University. It has been accepted for inclusion in Faculty Publications - Department of Electrical Engineering and Computer Science by an authorized administrator of Digital Commons @ George Fox University. For more information, please contact [email protected]. The Chirps Prototyping System Abstract Oregon State University has been a pioneer in developing a “Platform for Learning” using their TekBots platform as a fundamental part of their electrical and computer engineering curriculum. At George Fox University, we fundamentally affirm this concept of a “Platform for Learning,” but we additionally desire a “Platform for Prototyping.” By “Platform for Prototyping,” we mean a platform that will enable our engineering students to create significant engineering projects as part of a myriad of service-learning projects, student research, course projects, and the senior capstone experience. To be effective across our curriculum, this system must not only be usable by mechanical, electrical and computer engineers, but by engineering students at the end of their first year in the engineering program.
  • A Camera-Realistic Robotics Simulator for Cinematographic Purposes

    A Camera-Realistic Robotics Simulator for Cinematographic Purposes

    2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) October 25-29, 2020, Las Vegas, NV, USA (Virtual) CinemAirSim: A Camera-Realistic Robotics Simulator for Cinematographic Purposes Pablo Pueyo, Eric Cristofalo, Eduardo Montijano, and Mac Schwager Abstract— Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular in the film and entertainment industries, in part because of their maneuverability and perspectives they en- able. While there exists methods for controlling the position and orientation of the drones for visibility, other artistic elements of the filming process, such as focal blur, remain unexplored in the robotics community. The lack of cinematographic robotics solutions is partly due to the cost associated with the cameras and devices used in the filming industry, but also because state- of-the-art photo-realistic robotics simulators only utilize a full in-focus pinhole camera model which does not incorporate these desired artistic attributes. To overcome this, the main contribution of this work is to endow the well-known drone simulator, AirSim, with a cinematic camera as well as extend its API to control all of its parameters in real time, including various filming lenses and common cinematographic properties. Fig. 1. CinemAirSim allows to simulate a cinematic camera inside AirSim. In this paper, we detail the implementation of our AirSim Users can control lens parameters like the focal length, focus distance or modification, CinemAirSim, present examples that illustrate aperture, in real time. The figure shows a reproduction of a scene from “The the potential of the new tool, and highlight the new research Revenant”. We illustrate the filming drone (top left), the current camera opportunities that the use of cinematic cameras can bring to parameters (top right), the movie frame (bottom left) and simulated frame research in robotics and control.
  • ORCA - a Physics-Based Robotics Simulation Environment That Supports Distributed Systems Development

    ORCA - a Physics-Based Robotics Simulation Environment That Supports Distributed Systems Development

    Journal of Software Engineering for Robotics 5(2), September 2014, 13-24 ISSN: 2035-3928 ORCA - a physics-based robotics simulation environment that supports distributed systems development E. Hourdakis1 G. Chliveros1 P. Trahanias1;2 1 Institute of Computer Science, Foundation for Research and Technology, Greece 2 Department of Computer Science, University of Crete, Greece Abstract—Physics-based simulation is becoming an indispensable tool in robotics research, since it enables the evaluation of algorithms in silico, even when the actual robot is not available. Due to this, it is considered a standard practice, prior to any deployment on hardware platforms, and an important part of the development activities in large-scale projects. To cope with this role, simulators must address additional issues related to large-scale model development, including multi-modal processing, provisions for algorithmic integration, and fast, scalable graphics. In the current paper we present ORCA, a versatile, physics-based robotics simulator that integrates a server and a simulation environment into one package. This type of architecture makes the sharing of resources a seamless task, promotes code re-use, and facilitates the integration of individual software modules. To demonstrate the software’s applicability, we discuss three different use-cases, in which ORCA was used at the heart of their development efforts. Index Terms—Physics simulation, robotics, sensor modeling, graphics, distributed processing. 1 INTRODUCTION starting to claim an increased share of the development activ- ities in robotics, which can involve large-scale and integrated UE to the upsurge in processing power, physics engines systems. As such, they must consider issues related to the and CAD modeling software, robotic simulators are D distributed nature of software workflow, for example the ability increasingly being used as a cost-free alternative to actual to facilitate algorithmic integration or process several complex robotic platforms [1], [2].
  • Design of a Low-Cost Unmanned Surface Vehicle for Swarm Robotics Research in Laboratory Environments

    Design of a Low-Cost Unmanned Surface Vehicle for Swarm Robotics Research in Laboratory Environments

    DESIGN OF A LOW-COST UNMANNED SURFACE VEHICLE FOR SWARM ROBOTICS RESEARCH IN LABORATORY ENVIRONMENTS by c Calvin Gregory A thesis submitted to the School of Graduate Studies in partial fulfilment of the requirements for the degree of Master of Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland October 2020 St. John's Newfoundland Abstract Swarm robotics is the study of groups of simple, typically inexpensive agents working collaboratively toward a common goal. Such systems offer several benefits over single- robot solutions: they are flexible, scalable, and robust to the failure of individual agents. The majority of existing work in this field has focused on robots operating in terrestrial environments but the benefits of swarm systems extend to applications in the marine domain as well. The current scarcity of marine robotics platforms suitable for swarm research is detrimental to progress in this field. Of the few that exist, no publicly available unmanned surface vehicles can operate in a laboratory environment; an indoor tank of water where the vessels, temperature, lighting, etc. can be observed and controlled at all times. Laboratory testing is a common intermediate step in the hardware validation of algorithms. This thesis details the design of the microUSV: a small, inexpensive, laboratory-based platform developed to fill this gap. The microUSV system was validated by performing laboratory testing of two algo- rithms: a waypoint-following controller and orbital retrieval. The waypoint-following controller was a simple PI controller implementation which corrects a vessel's speed and heading to seek predetermined goal positions. The orbital retrieval algorithm is a novel method for a swarm of unmanned surface vehicles to gather floating marine contaminants such as plastics.
  • Design Industrial Robotics Applications with MATLAB and Simulink

    Design Industrial Robotics Applications with MATLAB and Simulink

    Design Industrial Robotics Applications with MATLAB and Simulink Presenter Name Here Trends in Industrial Robotics Cobots Grow fastest in shipment terms with CAGR of 20% from 2017 - 2023 Growing trend toward compact robots Increasing share of units shipped in 2023 will be payload <10kg 40% of 80% of 82% of Articulated Robots SCARA Robots Cobots Source: Interact Analysis 2 Evolution of Industrial Robotics Technologies Full Autonomy AI-enabled robots High Autonomy Conditional Autonomy Partial Autonomy Cobot UR5 1st Cobot at Linatex, 2008 1961 Human Assistant Traditional Industrial Robots - Automation Unimate at GM, 1961 No Automation 1961 2008 2019- 3 Autonomous Industrial Robotics Systems Workflow Operates independently, without explicit instructions from a human Connect/Deploy Code Generation ROS Autonomous Algorithms Sense (Observe) Perceive (Orient) Plan (Decide) Control (Act) Encoder Camera Environment Localization Feedback Controls Understanding Force/Torque Contact Path Planning Decision Logic Sensor Switches Object Gain Scheduling Proximity Sensors Detection/Tracking Obstacle Avoidance Trajectory Control S1 S3 S2 Platform Prototype HW Physical Model Actuation Model Environ Model Production HW 4 What we’ll discuss today 01 Challenges in Industry Robot System Design 02 Model-Based Design for Autonomous System Case Study: Pick-and- 03 Place Manipulation Application 04 Concluding Remarks 5 What we’ll discuss today 01 Challenges in Industry Robot System Design 02 Model-Based Design for Autonomous System Case Study: Pick-and- 03 Place
  • Autonomous Underwater Surveillance Robot

    Autonomous Underwater Surveillance Robot

    IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 10, Issue 3, Ver. IV (May - Jun.2015), PP 53-61 www.iosrjournals.org Autonomous Underwater Surveillance Robot Shruti Nautiyal1, Anshuman Mehta2 1(UG Student, Department of ECE, Seemant Institute of Technology, Pithoragarh, Uttrakhand, India) 2(UG Student, Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, India) Abstract: The main objective is to create an interface that allows a person to drive a robot in water and capturing the view through a night camera (360 degrees). Mobile robotic platforms are becoming more and more popular, both in scientific research and in commercial settings. Robotic systems are useful for going places or performing tasks that are not suitable for humans to do. Robots are often able to precisely perform complicated or dangerous tasks with little or no human involvement. However, before a mobile robotic platform is able to be deployed, it must have a way of identifying where it is in relation to objects and obstacles around it. Often, this is being performed by using a visual system, such as a camera. However, just wiring a camera onto a robot is not sufficient. With many of the tasks that are given to a robotic system to perform, a great deal of precision is required to satisfactorily complete these tasks. This precision requires that the robot be given accurate information by the camera. Keywords: AUVs; centre of gravity; buoyancy; thrusters; ARDUINO Board; L298; HT 12E Encoder and 12D Decoder; 434 MHZ TXR & RXR I.
  • Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark

    Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark

    SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark Linxi Fan∗ Yuke Zhu∗ Jiren Zhu Zihua Liu Orien Zeng Anchit Gupta Joan Creus-Costa Silvio Savarese Li Fei-Fei Stanford Vision and Learning Lab (SVL) Department of Computer Science, Stanford University surreal.stanford.edu Abstract: Reproducibility has been a significant challenge in deep reinforcement learning and robotics research. Open-source frameworks and standardized bench- marks can serve an integral role in rigorous evaluation and reproducible research. We introduce SURREAL, an open-source scalable framework that supports state- of-the-art distributed reinforcement learning algorithms. We design a principled distributed learning formulation that accommodates both on-policy and off-policy learning. We demonstrate that SURREAL algorithms outperform existing open- source implementations in both agent performance and learning efficiency. We also introduce SURREAL Robotics Suite, an accessible set of benchmarking tasks in physical simulation for reproducible robot manipulation research. We provide extensive evaluations of SURREAL algorithms and establish strong baseline results. Keywords: Robot Manipulation, Reinforcement Learning, Distributed Learning Systems, Reproducible Research 1 Introduction Reinforcement learning (RL) has been an established framework in robotics to learn controllers via trial and error [1]. Classic reinforcement learning literature in robotics has largely relied on handcrafted features and shallow models [2, 3]. The recent success of deep neural networks in learning representations [4] has incentivized researchers to use them as powerful function approximators to tackle more complex control problems, giving rise to deep reinforcement learning [5, 6]. Prior work has explored the potentials of using deep RL for robot manipulation [7, 8]. Recently we have witnessed an increasing number of successful demonstrations of deep RL in simulated environments [9, 10, 11] and on real hardware [12, 13].
  • Design and Implementation of an Autonomous Robotics Simulator

    Design and Implementation of an Autonomous Robotics Simulator

    DESIGN AND IMPLEMENTATION OF AN AUTONOMOUS ROBOTICS SIMULATOR by Adam Carlton Harris A thesis submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering Charlotte 2011 Approved by: _______________________________ Dr. James M. Conrad _______________________________ Dr. Ronald R. Sass _______________________________ Dr. Bharat Joshi ii © 2011 Adam Carlton Harris ALL RIGHTS RESERVED iii ABSTRACT ADAM CARLTON HARRIS. Design and implementation of an autonomous robotics simulator. (Under the direction of DR. JAMES M. CONRAD) Robotics simulators are important tools that can save both time and money for developers. Being able to accurately and easily simulate robotic vehicles is invaluable. In the past two decades, corporations, robotics labs, and software development groups have released many robotics simulators to developers. Commercial simulators have proven to be very accurate and many are easy to use, however they are closed source and generally expensive. Open source simulators have recently had an explosion of popularity, but most are not easy to use. This thesis describes the design criteria and implementation of an easy to use open source robotics simulator. SEAR (Simulation Environment for Autonomous Robots) is designed to be an open source cross-platform 3D (3 dimensional) robotics simulator written in Java using jMonkeyEngine3 and the Bullet Physics engine. Users can import custom-designed 3D models of robotic vehicles and terrains to be used in testing their own robotics control code. Several sensor types (GPS, triple-axis accelerometer, triple-axis gyroscope, and a compass) have been simulated and early work on infrared and ultrasonic distance sensors as well as LIDAR simulators has been undertaken.
  • Mixed Reality Technologies for Novel Forms of Human-Robot Interaction

    Mixed Reality Technologies for Novel Forms of Human-Robot Interaction

    Dissertation Mixed Reality Technologies for Novel Forms of Human-Robot Interaction Dissertation with the aim of achieving a doctoral degree at the Faculty of Mathematics, Informatics and Natural Sciences Dipl.-Inf. Dennis Krupke Human-Computer Interaction and Technical Aspects of Multimodal Systems Department of Informatics Universität Hamburg November 2019 Review Erstgutachter: Prof. Dr. Frank Steinicke Zweitgutachter: Prof. Dr. Jianwei Zhang Drittgutachter: Prof. Dr. Eva Bittner Vorsitzende der Prüfungskomission: Prof. Dr. Simone Frintrop Datum der Disputation: 17.08.2020 “ My dear Miss Glory, Robots are not people. They are mechanically more perfect than we are, they have an astounding intellectual capacity, but they have no soul.” Karel Capek Abstract Nowadays, robot technology surrounds us and future developments will further increase the frequency of our everyday contacts with robots in our daily life. To enable this, the current forms of human-robot interaction need to evolve. The concept of digital twins seems promising for establishing novel forms of cooperation and communication with robots and for modeling system states. Machine learning is now ready to be applied to a multitude of domains. It has the potential to enhance artificial systems with capabilities, which so far are found in natural intelligent creatures, only. Mixed reality experienced a substantial technological evolution in recent years and future developments of mixed reality devices seem to be promising, as well. Wireless networks will improve significantly in the next years and thus, latency and bandwidth limitations will be no crucial issue anymore. Based on the ongoing technological progress, novel interaction and communication forms with robots become available and their application to real-world scenarios becomes feasible.