Working Group Cognitive Robotics
|
|
- Olivia McBride
- 6 years ago
- Views:
Transcription
1 Working Group Cognitive Robotics Bernd Krieg-Brückner, Reinhard Moratz, Thomas Röfer, Kai Hübner, Axel Lankenau, Tilman Vierhuff Bremen Institute of Safe Systems Center for Computing Technology Universität Bremen
2 Overview System safety violated Safety module failure Collision Communication failure Active Collision Passive Collision Artificial Events FAULT TREE SAFETY MECHANISMS Artificial Events Release/ Block Relevant Events ENVIRONMENT+ EUC Reality Spatial Cognition Safe Robotics Safe Wheelchair RoboCup SLAM Navigation Assistant Working Group Cognitive Robotics 2
3 Rolland Technical Information Meyra Model Genius cm/s maximum speed Communication via two serial ports Sensor Equipment Internal sensors (speed/steering angle) 27 ultrasonic sensors (Nomadic) On-Board Computer Industry-PC (Pentium III/600) QNX (real-time operating system) Working Group Cognitive Robotics 3
4 Safe Wheelchair Motivation drive command via joystick sonar measurments of environment safety module safe drive command Working Group Cognitive Robotics 4
5 Safe Wheelchair Architecture real-time applications asynchronous applications network 32 ms sense & actuate modul (SAM) wheelchair Working Group Cognitive Robotics 5
6 Safe Wheelchair Static Fire Sequence Working Group Cognitive Robotics 6
7 Safe Wheelchair Static Fire Sequence (in motion) Working Group Cognitive Robotics 7
8 Safe Wheelchair Obstacle Detection age age of of measurement occupancy of of cell cell never never measured measured empty empty obstacle obstacle supposed supposed obstacle obstacle confirmed confirmed danger of of collision! Working Group Cognitive Robotics 8
9 Safe Wheelchair Results Working Group Cognitive Robotics 9
10 Driving Assistant Avoidance Working Group Cognitive Robotics 10
11 Driving Assistant Demonstration Working Group Cognitive Robotics 11
12 Overview System safety violated Safety module failure Collision Communication failure Active Collision Passive Collision Artificial Events FAULT TREE SAFETY MECHANISMS Artificial Events Release/ Block Relevant Events ENVIRONMENT+ EUC Spatial Cognition Safe Robotics Safe Wheelchair Reality RoboCup SLAM Navigation Assistant Working Group Cognitive Robotics 12
13 Navigation Assistant Marauder s Map Working Group Cognitive Robotics 13
14 Navigation Assistant Rolland acoustic instructions Turn right at the next possibility user interface visual instructions Working Group Cognitive Robotics 14
15 Generalization of Locomotion 224cm, 75, 799cm, -83, 880cm, -87, 260cm Working Group Cognitive Robotics 15
16 Modeling the Environment I H B C Junction DCI D G A E F Working Group Cognitive Robotics 16
17 Junctions Angle between incoming and outgoing segment Length of outgoing segment List of incoming segments A 90 1 m B A 1 m B 0 A 1 m B B -90 1,5 m A 1 m B 1,5 m C -90 C Crossing Junction Working Group Cognitive Robotics 17
18 Inductive Approach Idea: Assigning route corners to junctions Two-step assignment Corner matches a junction The rest of the generalized route matches up to the junction I H B C D G generalization of driven route A route graph E F Working Group Cognitive Robotics 18
19 Probabilities from Similarities probability probability angle difference (radians) corridor length (cm) route segment length (cm) Working Group Cognitive Robotics 19
20 Matching Corners Differentiation between the probabilities that the corner previously generalized really exists, Angle of corner is similar to angle of the junction in the route graph... the corner has been detected erroneously,... Angle of corner is similar to 0... a corner has been overlooked,... Angle of the junction in the route graph is similar to 0... it has been turned around at the corner previously generalized Angle of corner is similar to 180 route route graph Working Group Cognitive Robotics 20
21 Propagation of Probabilities = t+1 t t Working Group Cognitive Robotics 21
22 Determining the Candidate Junction Working Group Cognitive Robotics 22
23 Indoor and Outdoor Navigation Building: MZH Working Group Cognitive Robotics 23
24 Indoor and Outdoor Navigation Building: NW 2 Working Group Cognitive Robotics 24
25 Indoor and Outdoor Navigation Buildings: IW + BIBA Working Group Cognitive Robotics 25
26 Indoor and Outdoor Navigation Building: MZH Overall length: 2176 m Working Group Cognitive Robotics 26
27 Odometry Data NW2 FZB IW MZH Working Group Cognitive Robotics 27
28 Route Graph Working Group Cognitive Robotics 28
29 Results I Believed in previous corner Not believed in previous corner Most probable position Intensity encodes confidence Speeded up by factor 70 Working Group Cognitive Robotics 29
30 Working Group Cognitive Robotics 30 Universität Bremen Reference: Laser Scan Map t o p n q r m l k d c P M a WX Z T R L U S V h J D f i e Y g b C G Q I NO K H s F E j A B
31 Results II Working Group Cognitive Robotics 31
32 Overview System safety violated Safety module failure Collision Communication failure Active Collision Passive Collision Artificial Events FAULT TREE SAFETY MECHANISMS Artificial Events Release/ Block Relevant Events ENVIRONMENT+ EUC Spatial Cognition Safe Robotics Safe Wheelchair Reality RoboCup SLAM Navigation Assistant Working Group Cognitive Robotics 32
33 Our Teams Simulation League Small-Size League Sony Legged Robot League BUGS B-SMART Working Group Cognitive Robotics 33
34 Tasks S en s o r D at a S en s o r D at ap r o c es s o r C amer am at r ix Image ImageP r o c es s o r B lo b C o l lec t io n sensor processing B o d y P er c ep t P lay er s P er c ep t o r L in es P er c ep t o r P lay er s P er c ep t L in es P er c ep t L an d mar k s P er c ep t o r L an d mar k s P er c ep t B all P er c ep t o r B allp er c ep t object recognition R o b o t S t at ed et ec t o r R o b o t S t at e P lay er s L o c at o r P lay er P o s ec o llec t io n S elf L o c at o r R o b o t P o s e B alll o c at o r B allp o s it io n object modeling L E D R eq u es t B eh av io r C o n t r o l H ead C o n t r o lm o d e M o t io n R eq u es t behavior control L E D C o n t r o l H ead C o n t r o l M o t io n C o n t r o l motion control L E D V alu e H ead M o t io n R eq u es t J o in t D at ab u f f er O d o met r y D at a Working Group Cognitive Robotics 34
35 Process Layouts Input Robot Ball SelfLoc Players Debug Behavior Output Bremen Byters Process layout of the Bremen Byters Cognition Robot Debug Motion Humboldt 2002 Process layout of the Humboldt Heroes Working Group Cognitive Robotics 35
36 GermanTeam 2002 SimRobot RobotControl Working Group Cognitive Robotics 36
37 Localization Working Group Cognitive Robotics 37
38 Detecting Field Lines Working Group Cognitive Robotics 38
39 Projection on the Field Working Group Cognitive Robotics 39
40 Projection on the Field Working Group Cognitive Robotics 40
41 Localization Working Group Cognitive Robotics 41
42 Assigning Observations to Field Model Yellow Goal Lines Skyblue Goal Border Working Group Cognitive Robotics 42
43 Demo Working Group Cognitive Robotics 43
44 Impressions from Fukuoka Working Group Cognitive Robotics 44
45 Results of the GermanTeam Round Robin CMU GermanTeam Rome 5 : 0 CMU Rome 7 : 0 GermanTeam Tokyo 4 : 0 CMU Tokyo 5 : 1 GermanTeam CMU 1 : 3 CMU GeorgiaTech 7 : 0 GermanTeam GeorgiaTech 4 : 1 CMU Team Sweden 9 : 0 Quarterfinal CMU Melbourne 4 : 0 GermanTeam UNSW 1 : 6 UNSW UNSW Kyushu 7 : 0 UNSW Balkan 16 : 0 UNSW Washington 10 : 0 UNSW NewCastle 3 : 0 Final CMU UNSW 3 : 3 (5 : 4) Working Group Cognitive Robotics 45
46 Outlook Rolland Simultaneous localization and mapping (SLAM) Place integration Integration of additional sensor measurements Human-machine dialogs Augmenting maps by user interaction RoboCup RESEARCH CENTER Probabilistic world modeling and behavior German Open 2003 (Paderborn) WM in Padua, Italien Working Group Cognitive Robotics 46
47 For Further Information Working Group Cognitive Robotics 47
Introduction to Mobile Robotics Information Gain-Based Exploration. Wolfram Burgard, Cyrill Stachniss, Maren Bennewitz, Giorgio Grisetti, Kai Arras
Introduction to Mobile Robotics Information Gain-Based Exploration Wolfram Burgard, Cyrill Stachniss, Maren Bennewitz, Giorgio Grisetti, Kai Arras 1 Tasks of Mobile Robots mapping SLAM localization integrated
More informationVision for Mobile Robot Navigation: A Survey
Vision for Mobile Robot Navigation: A Survey (February 2002) Guilherme N. DeSouza & Avinash C. Kak presentation by: Job Zondag 27 February 2009 Outline: Types of Navigation Absolute localization (Structured)
More informationMulti-Sensor Fusion for Localization of a Mobile Robot in Outdoor Environments
Multi-Sensor Fusion for Localization of a Mobile Robot in Outdoor Environments Thomas Emter, Arda Saltoğlu and Janko Petereit Introduction AMROS Mobile platform equipped with multiple sensors for navigation
More informationMobile Robots Localization
Mobile Robots Localization Institute for Software Technology 1 Today s Agenda Motivation for Localization Odometry Odometry Calibration Error Model 2 Robotics is Easy control behavior perception modelling
More informationTowards Fully-automated Driving
Towards Fully-automated Driving Challenges and Potential Solutions Dr. Gijs Dubbelman Mobile Perception Systems EE-SPS/VCA Mobile Perception Systems 6 PhDs, postdoc, project manager, software engineer,
More informationNEURAL NETWORK WITH VARIABLE TYPE CONNECTION WEIGHTS FOR AUTONOMOUS OBSTACLE AVOIDANCE ON A PROTOTYPE OF SIX-WHEEL TYPE INTELLIGENT WHEELCHAIR
International Journal of Innovative Computing, Information and Control ICIC International c 2006 ISSN 1349-4198 Volume 2, Number 5, October 2006 pp. 1165 1177 NEURAL NETWORK WITH VARIABLE TYPE CONNECTION
More informationDIGITAL TWINS W A Z U G D e c e m b e r
DIGITAL TWINS W A Z U G - 1 3 D e c e m b e r 2 0 1 8 J o h a n H o e k J o h a n. H o e k @ W i n v i s i o n. n l F r a n k v a n H o u t e n F r a n k. v a n H o u t e n @ W i n v i s i o n. n l D E
More informationGradient Sampling for Improved Action Selection and Path Synthesis
Gradient Sampling for Improved Action Selection and Path Synthesis Ian M. Mitchell Department of Computer Science The University of British Columbia November 2016 mitchell@cs.ubc.ca http://www.cs.ubc.ca/~mitchell
More informationStigmergic navigation on an RFID floor with a multi-robot team Ali Abdul Khaliq Maurizio Di Rocco Alessandro Saffiotti
Stigmergic navigation on an RFID floor with a multi-robot team Ali Abdul Khaliq Maurizio Di Rocco Alessandro Saffiotti AASS Cognitive Robotic Systems Lab University of Örebro, Sweden 1 Motivation Stigmergy
More informationThe Reflexxes Motion Libraries. An Introduction to Instantaneous Trajectory Generation
ICRA Tutorial, May 6, 2013 The Reflexxes Motion Libraries An Introduction to Instantaneous Trajectory Generation Torsten Kroeger 1 Schedule 8:30-10:00 Introduction and basics 10:00-10:30 Coffee break 10:30-11:30
More informationpursues interdisciplinary long-term research in Spatial Cognition. Particular emphasis is given to:
The Transregional Collaborative Research Center SFB/TR 8 Spatial Cognition: Reasoning, Action, Interaction at the Universities of Bremen and Freiburg, Germany pursues interdisciplinary long-term research
More informationA First Attempt of Reservoir Pruning for Classification Problems
A First Attempt of Reservoir Pruning for Classification Problems Xavier Dutoit, Hendrik Van Brussel, Marnix Nuttin Katholieke Universiteit Leuven - P.M.A. Celestijnenlaan 300b, 3000 Leuven - Belgium Abstract.
More informationCOMP3411: Artificial Intelligence 7a. Evolutionary Computation
COMP3411 14s1 Evolutionary Computation 1 COMP3411: Artificial Intelligence 7a. Evolutionary Computation Outline Darwinian Evolution Evolutionary Computation paradigms Simulated Hockey Evolutionary Robotics
More informationLarge Scale Environment Partitioning in Mobile Robotics Recognition Tasks
Large Scale Environment in Mobile Robotics Recognition Tasks Boyan Bonev, Miguel Cazorla {boyan,miguel}@dccia.ua.es Robot Vision Group Department of Computer Science and Artificial Intelligence University
More informationCSE 473: Artificial Intelligence
CSE 473: Artificial Intelligence Hidden Markov Models Dieter Fox --- University of Washington [Most slides were created by Dan Klein and Pieter Abbeel for CS188 Intro to AI at UC Berkeley. All CS188 materials
More informationA Quantum Computing Approach to the Verification and Validation of Complex Cyber-Physical Systems
A Quantum Computing Approach to the Verification and Validation of Complex Cyber-Physical Systems Achieving Quality and Cost Control in the Development of Enormous Systems Safe and Secure Systems and Software
More informationState Space Search Problems
State Space Search Problems Lecture Heuristic Search Stefan Edelkamp 1 Overview Different state space formalisms, including labelled, implicit and explicit weighted graph representations Alternative formalisms:
More informationProbability Map Building of Uncertain Dynamic Environments with Indistinguishable Obstacles
Probability Map Building of Uncertain Dynamic Environments with Indistinguishable Obstacles Myungsoo Jun and Raffaello D Andrea Sibley School of Mechanical and Aerospace Engineering Cornell University
More informationELEC4631 s Lecture 2: Dynamic Control Systems 7 March Overview of dynamic control systems
ELEC4631 s Lecture 2: Dynamic Control Systems 7 March 2011 Overview of dynamic control systems Goals of Controller design Autonomous dynamic systems Linear Multi-input multi-output (MIMO) systems Bat flight
More informationMechanical Simulation Of The ExoMars Rover Using Siconos in 3DROV
V. Acary, M. Brémond, J. Michalczyk, K. Kapellos, R. Pissard-Gibollet 1/15 Mechanical Simulation Of The ExoMars Rover Using Siconos in 3DROV V. Acary, M. Brémond, J. Michalczyk, K. Kapellos, R. Pissard-Gibollet
More informationReasoning Under Uncertainty Over Time. CS 486/686: Introduction to Artificial Intelligence
Reasoning Under Uncertainty Over Time CS 486/686: Introduction to Artificial Intelligence 1 Outline Reasoning under uncertainty over time Hidden Markov Models Dynamic Bayes Nets 2 Introduction So far we
More informationAlgorithmic verification
Algorithmic verification Ahmed Rezine IDA, Linköpings Universitet Hösttermin 2018 Outline Overview Model checking Symbolic execution Outline Overview Model checking Symbolic execution Program verification
More informationA Review of Kuiper s: Spatial Semantic Hierarchy
A Review of Kuiper s: Spatial Semantic Hierarchy Okuary Osechas Comp-150: Behavior Based Robotics 4 November 2010 Outline Introduction 1 Introduction 2 Summary of ideas 3 Ontological Levels 4 Interfacing
More informationAn Adaptive Clustering Method for Model-free Reinforcement Learning
An Adaptive Clustering Method for Model-free Reinforcement Learning Andreas Matt and Georg Regensburger Institute of Mathematics University of Innsbruck, Austria {andreas.matt, georg.regensburger}@uibk.ac.at
More informationSpatial Cognition: From Rat-Research to Multifunctional Spatial Assistance Systems
Spatial Cognition: From Rat-Research to Multifunctional Spatial Assistance Systems Markus Knauff, Christoph Schlieder, Christian Freksa Spatial cognition research is making rapid progress in understanding
More informationLego NXT: Navigation and localization using infrared distance sensors and Extended Kalman Filter. Miguel Pinto, A. Paulo Moreira, Aníbal Matos
Lego NXT: Navigation and localization using infrared distance sensors and Extended Kalman Filter Miguel Pinto, A. Paulo Moreira, Aníbal Matos 1 Resume LegoFeup Localization Real and simulated scenarios
More informationCollaborative topic models: motivations cont
Collaborative topic models: motivations cont Two topics: machine learning social network analysis Two people: " boy Two articles: article A! girl article B Preferences: The boy likes A and B --- no problem.
More informationIntroduction to Mobile Robotics SLAM: Simultaneous Localization and Mapping
Introduction to Mobile Robotics SLAM: Simultaneous Localization and Mapping Wolfram Burgard, Cyrill Stachniss, Kai Arras, Maren Bennewitz What is SLAM? Estimate the pose of a robot and the map of the environment
More informationSOFTWARE. Control of the AMS SYSTEM CONTROL AND MONITORING OF AIRFIELD GROUND LIGHTING EQUIPMENT
Control of the AMS SYSTEM SOFTWARE CONTROL AND MONITORING OF AIRFIELD GROUND LIGHTING EQUIPMENT Description of function airfield ground lighting equipment are shown on the screen representing the airport
More informationInstallation guide 862 MIT / MIR
Installation guide 862 MIT / MIR in combination with: 864 MTT or 863 MRT or (dual) spot element November 2005 Part no. 4416.232_Rev3 Enraf BV PO Box 812 2600 AV Delft Netherlands Tel. : +31 15 2701 100
More informationCOMP3411: Artificial Intelligence 10a. Evolutionary Computation
COMP3411 16s1 Evolutionary Computation 1 COMP3411: Artificial Intelligence 10a. Evolutionary Computation Outline Darwinian Evolution Evolutionary Computation paradigms Simulated Hockey Evolutionary Robotics
More informationUnit Modules. Daniela Rus, Marsette Vona Department of Computer Science Dartmouth College Hanover, NH. Presented by Matthew Aldridge
Crystalline Robots: Selfreconfiguration with Compressible Unit Modules Daniela Rus, Marsette Vona Department of Computer Science Dartmouth College Hanover, NH Presented by Matthew Aldridge Introduction
More informationModeling and state estimation Examples State estimation Probabilities Bayes filter Particle filter. Modeling. CSC752 Autonomous Robotic Systems
Modeling CSC752 Autonomous Robotic Systems Ubbo Visser Department of Computer Science University of Miami February 21, 2017 Outline 1 Modeling and state estimation 2 Examples 3 State estimation 4 Probabilities
More informationGIS-based Smart Campus System using 3D Modeling
GIS-based Smart Campus System using 3D Modeling Smita Sengupta GISE Advance Research Lab. IIT Bombay, Powai Mumbai 400 076, India smitas@cse.iitb.ac.in Concept of Smart Campus System Overview of IITB Campus
More informationChris Elliott Flight Controls / Quantum Computing. Copyright 2015, Lockheed Martin Corporation. All rights reserved.
On Example Models and Challenges Ahead for the Evaluation of Complex Cyber-Physical Systems with State of the Art Formal Methods V&V Research in Quantum Enabled V&V Technology June 9-11, 2015 Chris Elliott
More informationThe Belief Roadmap: Efficient Planning in Belief Space by Factoring the Covariance. Samuel Prentice and Nicholas Roy Presentation by Elaine Short
The Belief Roadmap: Efficient Planning in Belief Space by Factoring the Covariance Samuel Prentice and Nicholas Roy Presentation by Elaine Short 1 Outline" Motivation Review of PRM and EKF Factoring the
More informationPartially Observable Markov Decision Processes (POMDPs)
Partially Observable Markov Decision Processes (POMDPs) Sachin Patil Guest Lecture: CS287 Advanced Robotics Slides adapted from Pieter Abbeel, Alex Lee Outline Introduction to POMDPs Locally Optimal Solutions
More informationTSRT14: Sensor Fusion Lecture 9
TSRT14: Sensor Fusion Lecture 9 Simultaneous localization and mapping (SLAM) Gustaf Hendeby gustaf.hendeby@liu.se TSRT14 Lecture 9 Gustaf Hendeby Spring 2018 1 / 28 Le 9: simultaneous localization and
More informationAS STANDARD
AS 1319-1994 STANDARD SAFETY SIGNS FOR THE OCCUPATIONAL ENVIRONMENT COMPLIES WI TH THE ST ANDARDS AUST RAL I A COMMITTEE INDU ST RI AL WARNI NG SIG N S Safety Signs are crucial in any work environment.
More informationParticle Filters; Simultaneous Localization and Mapping (Intelligent Autonomous Robotics) Subramanian Ramamoorthy School of Informatics
Particle Filters; Simultaneous Localization and Mapping (Intelligent Autonomous Robotics) Subramanian Ramamoorthy School of Informatics Recap: State Estimation using Kalman Filter Project state and error
More informationPage 1. A Grieg Group Company
Page 1 ECDIS PAST, PRESENT & Future 2000-2010 Past Present 2010-2015 2015... Future Page 2 History Page 3 DEEPLY - Past What is going on there????? I am Checking now Sir Page 4 ECDIS History ECDIS has
More informationSLAM for Ship Hull Inspection using Exactly Sparse Extended Information Filters
SLAM for Ship Hull Inspection using Exactly Sparse Extended Information Filters Matthew Walter 1,2, Franz Hover 1, & John Leonard 1,2 Massachusetts Institute of Technology 1 Department of Mechanical Engineering
More informationInstrumentation Commande Architecture des Robots Evolués
Instrumentation Commande Architecture des Robots Evolués Program 4a : Automatic Control, Robotics, Signal Processing Presentation General Orientation Research activities concern the modelling and control
More informationPlasma: A new SMC Checker. Axel Legay. In collaboration with L. Traonouez and S. Sedwards.
Plasma: A new SMC Checker Axel Legay In collaboration with L. Traonouez and S. Sedwards. 1 Plasma Lab A PLAtform for Statistical Model Analysis A library of statistical model-checking algorithms (Monte-Carlo,
More informationTopic 9 Potential fields: Follow your potential
Topic 9 Potential fields: Follow your potential Path Planning B: Goal Find intermediate poses forming a path to the goal ) How can we find such paths? 2) Define pose and controls? Path on a graph: vertices
More informationTwo Fundamental Functions of a Robot
Two Fundamental Functions of a Robot 2 Mobile Robotics About control of an autonomous or semi-autonomous vehicle About understanding of (large-scale) space Sensing about Reasoning about Moving through
More informationNetwork Algorithms and Complexity (NTUA-MPLA) Reliable Broadcast. Aris Pagourtzis, Giorgos Panagiotakos, Dimitris Sakavalas
Network Algorithms and Complexity (NTUA-MPLA) Reliable Broadcast Aris Pagourtzis, Giorgos Panagiotakos, Dimitris Sakavalas Slides are partially based on the joint work of Christos Litsas, Aris Pagourtzis,
More informationUsing the Kalman Filter for SLAM AIMS 2015
Using the Kalman Filter for SLAM AIMS 2015 Contents Trivial Kinematics Rapid sweep over localisation and mapping (components of SLAM) Basic EKF Feature Based SLAM Feature types and representations Implementation
More informationDistributed Robust Localization from Arbitrary Initial Poses via EM and Model Selection
1 Distributed Robust Localization from Arbitrary Initial Poses via EM and Model Selection Vadim Indelman Collaborators: Erik Nelson, Jing Dong, Nathan Michael and Frank Dellaert IACAS, February 15 Collaborative
More informationInter-Vehicle Safety by Transponder Based Localization
Inter-Vehicle Safety by Transponder Based Localization Fahrzeug-Fahrzeug-Sicherheit durch transponderbasierte Ortung Erich Lankes Daimler AG Phases of Sensorrevolution Ko-TAG Phase I Monitoring of vehicle
More informationQuantum Computing Approach to V&V of Complex Systems Overview
Quantum Computing Approach to V&V of Complex Systems Overview Summary of Quantum Enabled V&V Technology June, 04 Todd Belote Chris Elliott Flight Controls / VMS Integration Discussion Layout I. Quantum
More informationLecture 4: Perceptrons and Multilayer Perceptrons
Lecture 4: Perceptrons and Multilayer Perceptrons Cognitive Systems II - Machine Learning SS 2005 Part I: Basic Approaches of Concept Learning Perceptrons, Artificial Neuronal Networks Lecture 4: Perceptrons
More informationPOE FINAL SEMESTER 2
POE FINAL SEMESTER 2 MULTIPLE CHOICE 1. What is the purpose of the RobotC Debug window? a. It allows the user to Start and Stop their program. b. It allows the user to step through their program one line
More informationEXPERIMENTS IN ROBOT FORMATION CONTROL WITH AN EMPHASIS ON DECENTRALIZED CONTROL ALGORITHMS. Joshua Cook. B.S., Kansas State University, 2008 A THESIS
EXPERIMENTS IN ROBOT FORMATION CONTROL WITH AN EMPHASIS ON DECENTRALIZED CONTROL ALGORITHMS by Joshua Cook B.S., Kansas State University, 2008 A THESIS submitted in partial fulfillment of the requirements
More informationMobile Robot Localization
Mobile Robot Localization 1 The Problem of Robot Localization Given a map of the environment, how can a robot determine its pose (planar coordinates + orientation)? Two sources of uncertainty: - observations
More informationTowards Automatic Nanomanipulation at the Atomic Scale
Towards Automatic Nanomanipulation at the Atomic Scale Bernd Schütz Department of Computer Science University of Hamburg, Germany Department of Computer Science Outline Introduction System Overview Workpackages
More informationCS599 Lecture 1 Introduction To RL
CS599 Lecture 1 Introduction To RL Reinforcement Learning Introduction Learning from rewards Policies Value Functions Rewards Models of the Environment Exploitation vs. Exploration Dynamic Programming
More informationRobotics 2 AdaBoost for People and Place Detection
Robotics 2 AdaBoost for People and Place Detection Giorgio Grisetti, Cyrill Stachniss, Kai Arras, Wolfram Burgard v.1.0, Kai Arras, Oct 09, including material by Luciano Spinello and Oscar Martinez Mozos
More informationMotion Control of Passive Haptic Device Using Wires with Servo Brakes
The IEEE/RSJ International Conference on Intelligent Robots and Systems October 8-,, Taipei, Taiwan Motion Control of Passive Haptic Device Using Wires with Servo Brakes Yasuhisa Hirata, Keitaro Suzuki
More informationr. Matthias Bretschneider amburg - Dept. Safety Fehleranalyse mit Hilfe von Model Checkern
r. Matthias Bretschneider amburg - Dept. Safety Fehleranalyse mit Hilfe von Model Checkern otivation: Design of safe embedded systems X y Sensor(s) Controller Actuator Design Phase Study the effect of
More informationChapter 1 Introduction
Chapter 1 Introduction 1.1 Introduction to Chapter This chapter starts by describing the problems addressed by the project. The aims and objectives of the research are outlined and novel ideas discovered
More informationarxiv: v1 [cs.ro] 31 Jan 2018
Naive Bayes Entrapment Detection for Planetary Rovers Dicong Qiu dq@cs.cmu.edu Carnegie Mellon University arxiv:1801.10571v1 [cs.ro] 31 Jan 2018 Abstract Entrapment detection is a prerequisite for planetary
More informationAP Statistics Ch 6 Probability: The Study of Randomness
Ch 6.1 The Idea of Probability Chance behavior is unpredictable in the short run but has a regular and predictable pattern in the long run. We call a phenomenon random if individual outcomes are uncertain
More informationFault Tolerance of a Reconfigurable Autonomous Goal-Based Robotic Control System
Fault Tolerance of a Reconfigurable Autonomous Goal-Based Robotic Control System Julia M. B. Braman, David A. Wagner, and Richard M. Murray Abstract Fault tolerance is essential for the success of autonomous
More informationGeoWorlds: Integrated Digital Libraries and Geographic Information Systems
GeoWorlds: Integrated Digital Libraries and Geographic Information Systems http://www.isi.edu/geoworlds Robert Neches In-Young Ko, Robert MacGregor, Ke-Thia Yao Distributed Scalable Systems Division USC
More informationMeasurement of Bone Strength and Stiffness using 3-Point Bending
BME 315 Biomechanics, U. Wisconsin Adapted by R. Lakes from D. Thelen and C. Decker, 09, adapted from Lakes 06 Experimental Details I. Laboratory equipment The load frame that we will use to perform our
More informationInstitute of Optical Sensor Systems German Aerospace Center
DLR.de Chart 1 Institute of Optical Sensor Systems German Aerospace Center Dr. Anko Börner Institute of Optical Sensor Systems 15th February 2017 DLR.de Chart 2 DLR Deutsches Zentrum für Luft- und Raumfahrt
More informationData Informatics. Seon Ho Kim, Ph.D.
Data Informatics Seon Ho Kim, Ph.D. seonkim@usc.edu What is Machine Learning? Overview slides by ETHEM ALPAYDIN Why Learn? Learn: programming computers to optimize a performance criterion using example
More informationVN-100 Velocity Compensation
VN-100 Velocity Compensation Velocity / Airspeed Aiding for AHRS Applications Application Note Abstract This application note describes how the VN-100 can be used in non-stationary applications which require
More information12 Review and Outlook
12 Review and Outlook 12.1 Review 12.2 Outlook http://www-kdd.isti.cnr.it/nwa Spatial Databases and GIS Karl Neumann, Sarah Tauscher Ifis TU Braunschweig 926 What are the basic functions of a geographic
More informationMomentum in Collisions
Activity 14 PS-2826 Momentum in Collisions Mechanics: momentum, impulse, conservation of momentum GLX setup file: momentum Qty Equipment and Materials Part Number 1 PASPORT Xplorer GLX PS-2002 2 PASPORT
More informationSafety analysis and standards Analyse de sécurité et normes Sicherheitsanalyse und Normen
Industrial Automation Automation Industrielle Industrielle Automation 9.6 Safety analysis and standards Analyse de sécurité et normes Sicherheitsanalyse und Normen Prof Dr. Hubert Kirrmann & Dr. B. Eschermann
More informationOn-Line TSA and Control at EMS Control Centers for Large Power Grids
On-Line TSA and Control at EMS Control Centers for Large Power Grids Dr. Hsiao-Dong Chiang (i) Prof. of School of Electrical and Computer Engineering, Cornell University, Ithaca, NY (ii) President of BSI,
More informationInstituto de Sistemas e Robótica. Pólo de Lisboa
Instituto de Sistemas e Robótica Pólo de Lisboa Visual Tracking for Mobile Robot Localization 1 Jose Neira 2 October 1996 RT-602-96 ISR-Torre Norte Av. Rovisco Pais 1096 Lisboa CODEX PORTUGAL 1 This work
More informationCreation and modification of a geological model Program: Stratigraphy
Engineering manual No. 39 Updated: 11/2018 Creation and modification of a geological model Program: Stratigraphy File: Demo_manual_39.gsg Introduction The aim of this engineering manual is to explain the
More informationMarkov Models. CS 188: Artificial Intelligence Fall Example. Mini-Forward Algorithm. Stationary Distributions.
CS 88: Artificial Intelligence Fall 27 Lecture 2: HMMs /6/27 Markov Models A Markov model is a chain-structured BN Each node is identically distributed (stationarity) Value of X at a given time is called
More informationEnrico Nardelli Logic Circuits and Computer Architecture
Enrico Nardelli Logic Circuits and Computer Architecture Appendix B The design of VS0: a very simple CPU Rev. 1.4 (2009-10) by Enrico Nardelli B - 1 Instruction set Just 4 instructions LOAD M - Copy into
More informationMathematics (JUN13MD0201) General Certificate of Education Advanced Level Examination June Unit Decision TOTAL.
Centre Number Candidate Number For Examiner s Use Surname Other Names Candidate Signature Examiner s Initials Mathematics Unit Decision 2 Thursday 13 June 2013 General Certificate of Education Advanced
More informationGS110. IR Thermal Imaging System for Low-Emissivity Glass with Automatic Emissivity Correction. Manual Addendum
GS110 IR Thermal Imaging System for Low-Emissivity Glass with Automatic Emissivity Correction Manual Addendum Rev. B 10/2006 1 Safety Instructions All notices regarding safety and acceptable operation
More informationEVOLVING PREDATOR CONTROL PROGRAMS FOR A HEXAPOD ROBOT PURSUING A PREY
EVOLVING PREDATOR CONTROL PROGRAMS FOR A HEXAPOD ROBOT PURSUING A PREY GARY PARKER, CONNECTICUT COLLEGE, USA, parker@conncoll.edu BASAR GULCU, CONNECTICUT COLLEGE, USA, bgul@conncoll.edu ABSTRACT Control
More informationArtificial Intelligence
Artificial Intelligence Roman Barták Department of Theoretical Computer Science and Mathematical Logic Summary of last lecture We know how to do probabilistic reasoning over time transition model P(X t
More informationGlobal Workspace Theory Inspired Architecture for Autonomous Structural Health Monitoring
Global Workspace Theory Inspired Architecture for Autonomous Structural Health Monitoring 31 July 12 A Framework for Incorporating Contextual Information to Improve Decision Making Multifunctional Materials
More informationReliability of Technical Systems
Reliability of Technical Systems Main Topics 1. Short Introduction, Reliability Parameters: Failure Rate, Failure Probability, etc. 2. Some Important Reliability Distributions 3. Component Reliability
More informationAssertions and Measurements for Mixed-Signal Simulation
Assertions and Measurements for Mixed-Signal Simulation PhD Thesis Thomas Ferrère VERIMAG, University of Grenoble (directeur: Oded Maler) Mentor Graphics Corporation (co-encadrant: Ernst Christen) October
More informationSherlock Tutorial Plated Through Hole (PTH) Fatigue Analysis
Sherlock Tutorial Plated Through Hole (PTH) Fatigue Analysis Background Plated Through Holes (PTHs), also known as plated through vias (PTVs), are holes drilled through multilayer printed circuit boards
More informationWest Hollywood Park / Community Center S T E E R I N G C O M M I T T E E M E E T I N G T H R E E J U L Y,
West Hollywood Park / Community Center S T E E R I N G C O M M I T T E E M E E T I N G T H R E E J U L Y, 2 0 1 4 1. 2. 3. 4. 5. Meeting Number One Programming Scope Definition Meeting Number Two Programming
More informationIntegrating Induction and Deduction for Verification and Synthesis
Integrating Induction and Deduction for Verification and Synthesis Sanjit A. Seshia Associate Professor EECS Department UC Berkeley DATE 2013 Tutorial March 18, 2013 Bob s Vision: Exploit Synergies between
More informationDANIEL WILSON AND BEN CONKLIN. Integrating AI with Foundation Intelligence for Actionable Intelligence
DANIEL WILSON AND BEN CONKLIN Integrating AI with Foundation Intelligence for Actionable Intelligence INTEGRATING AI WITH FOUNDATION INTELLIGENCE FOR ACTIONABLE INTELLIGENCE in an arms race for artificial
More informationCS 387/680: GAME AI MOVEMENT
CS 387/680: GAME AI MOVEMENT 4/11/2017 Instructor: Santiago Ontañón so367@drexel.edu Class website: https://www.cs.drexel.edu/~santi/teaching/2017/cs387/intro.html Outline Movement Basics Aiming Jumping
More informationCRANES STRUCTURE INSPECTION USING METAL MAGNETIC MEMORY METHOD
CRANES STRUCTURE INSPECTION USING METAL MAGNETIC MEMORY METHOD Agnieszka Kosoń-Schab AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Mickiewicza Avenue 30, 30-059
More informationMobile Robot Localization
Mobile Robot Localization 1 The Problem of Robot Localization Given a map of the environment, how can a robot determine its pose (planar coordinates + orientation)? Two sources of uncertainty: - observations
More informationCapacity Estimation. Based on Joe Mitchell s slides
Capacity Estimation Based on Joe Mitchell s slides Output: Capacity What is capacity? Estimate of number of aircraft that can be safely routed within a constrained airspace. Demand-driven capacity Sector-induced
More informationConsistent Triangulation for Mobile Robot Localization Using Discontinuous Angular Measurements
Seminar on Mechanical Robotic Systems Centre for Intelligent Machines McGill University Consistent Triangulation for Mobile Robot Localization Using Discontinuous Angular Measurements Josep M. Font Llagunes
More informationCS 5522: Artificial Intelligence II
CS 5522: Artificial Intelligence II Hidden Markov Models Instructor: Wei Xu Ohio State University [These slides were adapted from CS188 Intro to AI at UC Berkeley.] Pacman Sonar (P4) [Demo: Pacman Sonar
More informationDVClub Europe Formal fault analysis for ISO fault metrics on real world designs. Jörg Große Product Manager Functional Safety November 2016
DVClub Europe Formal fault analysis for ISO 26262 fault metrics on real world designs Jörg Große Product Manager Functional Safety November 2016 Page 1 11/27/2016 Introduction Functional Safety The objective
More informationData Sheet. Functional Safety Characteristic Safety Values for BE..(FS) Brakes * _0715*
Drive Technology \ Drive Automation \ System Integration \ Services *22292616_0715* Data Sheet Functional Safety Characteristic Safety Values for BE..(FS) Brakes Edition 07/2015 22292616/EN SEW-EURODRIVE
More informationProperty Checking of Safety- Critical Systems Mathematical Foundations and Concrete Algorithms
Property Checking of Safety- Critical Systems Mathematical Foundations and Concrete Algorithms Wen-ling Huang and Jan Peleska University of Bremen {huang,jp}@cs.uni-bremen.de MBT-Paradigm Model Is a partial
More informationRemote Display Unit. Installers Handbook Copyright 2001 AirSense Technology Ltd. LM Remote Display Unit Installers Handbook Issue 1.
Remote Display Unit Installers Handbook Copyright 2001 AirSense Technology Ltd AirSense, ClassiFire, FastLearn PipeCAD, SenseNET, Stratos-HSSD and Stratos-Quadra are trademarks. HSSD is a Registered Trademark.
More informationSimply Typed Lambda Calculus
Simply Typed Lambda Calculus Language (ver1) Lambda calculus with boolean values t ::= x variable x : T.t abstraction tt application true false boolean values if ttt conditional expression Values v ::=
More informationCo-evolution of Morphology and Control for Roombots
Co-evolution of Morphology and Control for Roombots Master Thesis Presentation Ebru Aydın Advisors: Prof. Auke Jan Ijspeert Rico Möckel Jesse van den Kieboom Soha Pouya Alexander Spröwitz Co-evolution
More information