170111 寄セ?ミ2

Jan 27, 20170 likes113 views

The document discusses the Robotics Laboratory at Wakayama University Graduate School of System Engineering. It outlines the laboratory's work with deep learning, ROS/MORSE simulation, force application, SLIM programming, SVM algorithms, tactile and force sensors, RFID, LRF, IMU, RGBD sensors. It also describes projects involving ROS-TMS, SmartPal V, and MORSE simulation. The laboratory researches topics such as grasping, localization, and navigation to advance robotics.

Robotics Laboratory
2
Wakayama University Graduate School of System Engineering Robotics Laboratory
?
?
?
?

Robotics Laboratory
3
Wakayama University Graduate School of System Engineering Robotics Laboratory
? ?
DL
? ?
ROS/MORSE ?
? ?
FA
https://www.openrobots.org/morse/doc/stable/user/robots/pr2.html

＾￣
FUJITSU, Vol.67, No.3, pp.39-44 2016
Robotics Laboratory
4
Wakayama University Graduate School of System Engineering Robotics Laboratory

?
?
?
? ?
?
RTM ROS
Robotics Laboratory
5
Wakayama University Graduate School of System Engineering Robotics Laboratory
?
?

? ?
? ?
☆ : 1 1
Robotics Laboratory
6
Wakayama University Graduate School of System Engineering Robotics Laboratory
?
?
?

Robotics Laboratory
7
Wakayama University Graduate School of System Engineering Robotics Laboratory
? ?
?
? ?
?
1. ?
2. ?
3.
?

Robotics Laboratory
8
Wakayama University Graduate School of System Engineering Robotics Laboratory
? ?
?
? ?
? ?
?
?
?

Robotics Laboratory
9
Wakayama University Graduate School of System Engineering Robotics Laboratory
? SLIM* ?
?
? ?
* SLIM : Standard Language?for ?
Industrial Manipulators?
(JIS B 8439:1992)
?

Robotics Laboratory
10
Wakayama University Graduate School of System Engineering Robotics Laboratory
? ?
?
? ?
?
?
?
? ?
SVM
?

Robotics Laboratory
11
Wakayama University Graduate School of System Engineering Robotics Laboratory
?
?
?
?
?

Robotics Laboratory
12
Wakayama University Graduate School of System Engineering Robotics Laboratory
＾ ?
￣
, 19 , pp.624-630 2014

Robotics Laboratory
13
Wakayama University Graduate School of System Engineering Robotics Laboratory
?
? ?
?
?
?

Robotics Laboratory
14
Wakayama University Graduate School of System Engineering Robotics Laboratory
?
? TMS ?
?
LRF ?
IMU ?
RFID ?
RGBD ?
?

Robotics Laboratory
15
Wakayama University Graduate School of System Engineering Robotics Laboratory
ROS-TMS
? ROS TMS ?
? LRF RFID ?
? ?
? Choreonoid + graspPlugin
?

Robotics Laboratory
16
Wakayama University Graduate School of System Engineering Robotics Laboratory
? SmartPal V Kinect RFID
? LRF RFID RFID
?
?
?

Robotics Laboratory
17
Wakayama University Graduate School of System Engineering Robotics Laboratory
[Fig.6] LRF ?
FSS
? ?
[Fig.7] RFID ?
? RFID ?
?

Robotics Laboratory
18
Wakayama University Graduate School of System Engineering Robotics Laboratory
TMS ROS-TMS ROS-TMS
? ROS ?
?
? ?
?

Robotics Laboratory
19
Wakayama University Graduate School of System Engineering Robotics Laboratory
? ?
?
DL
? ?
ROS/MORSE
? ?
FA

Robotics Laboratory
20
Wakayama University Graduate School of System Engineering Robotics Laboratory

ROS-TMS
Robotics Laboratory
21
Wakayama University Graduate School of System Engineering Robotics Laboratory
ROS-TMS
? ROS TMS ?
? ?
?
?
?
?

ROS-TMS
Robotics Laboratory
22
Wakayama University Graduate School of System Engineering Robotics Laboratory

Robotics Laboratory
23
Wakayama University Graduate School of System Engineering Robotics Laboratory

MORSE Simulator
? 4000
? 60000
? telnet
MORSE Simulator
Robotics Laboratory
24
Wakayama University Graduate School of System Engineering Robotics Laboratory

The document discusses setting up Apache web server and PostgreSQL database on a server. It provides commands to install and configure Apache to use a server name and set index files. It also provides commands to install and configure PostgreSQL, create a database and user, insert and query data from a table, then remove the table and database. The last page lists other technologies that could also be set up which include UIMA, MySQL and webmini.

161215robo_lab

170118　烏御喘robo_lab

The document describes the various software tools used in the Robotics Laboratory at Wakayama University Graduate School of System Engineering. It lists Ubuntu 16.04 LTS, PCL 1.8, MORSE Simulator 1.4, ROS Kinetic Kame, Blender 2.76, Python 3.5.2, Protege 5.1.0, Apache 2.4.18, PostgreSQL 9.5.5, Webmin 1.820, and Tomcat 8.5.9 as some of the key software packages. It also provides brief descriptions and instructions for tools like VLC, Kinect, PCL, Jetson TK1, ROS Turtle Sim, MORSE,

170126robo_lab

This document discusses robotics research being conducted at the Robotics Laboratory at Wakayama University Graduate School of System Engineering. It lists three references used in their research - a 2014 paper on robot control in the IHI Engineering Review journal, a 2009 paper on robot motion planning in the IEEE Transactions on Robotics journal, and the use of MoveIt! and Blender software for robotics projects. The document provides brief information about the Robotics Laboratory and references used to support their work.

170112robo_lab

This document provides instructions for installing and building the Point Cloud Library (PCL) on an Ubuntu system. It outlines downloading dependencies using apt-get, adding a PCL PPA repository, cloning the PCL GitHub repository, and running cmake and make to build and install PCL. The document also lists some related topics like PostgreSQL, Kinect, deep learning frameworks, robot simulators, and motion planning software that can be used with PCL.

161124robo_lab

The document discusses a robotics laboratory at Wakayama University Graduate School of System Engineering. It lists the software used in the laboratory, including Ubuntu 16.04 LTS, MORSE Simulator 1.4, ROS Kinetic Kame, Blender 2.76, Python 3.5.2, Pyenv, Anaconda 4.1.1, and Protege 5.1.0. It also mentions using the MORSE Simulator kitchen environment with a PR2 robot and the Protege Ontology tool.

161027robo_lab

This document provides an overview of the software and tools used in the Robotics Laboratory at Wakayama University Graduate School of System Engineering. It details the use of 3 Kinect sensors, CNN, TensorFlow, Caffe and other deep learning tools. It also lists the software installed including Ubuntu 16.04, ROS Kinetic, Blender 2.76, Python 2.7 and 3.5, Pyenv, Anaconda and the MORSE simulator for developing and testing robotics applications.

161020robo_lab

161201robo_lab

RAIOT- Robotics Automation & Internet of Things Lab ReportVishal Aditya

The document describes projects being conducted at the Robotics Automation & Internet of Things Lab (RAIOT Lab) at Amity University Rajasthan. The RAIOT Lab focuses on hands-on learning and research related to robotics and IoT. Current projects include developing a 17 DOF humanoid robot, soccer playing robot, remote controlled race car, combat robot for robot wars competitions, and gesture controlled robot. The lab is also working on automation projects like a hand gesture controlled game simulator and an EEG-based game simulator. The goal is to enhance gaming experiences using affordable technologies.

A presentation on obstacle avoiding robotkantankit4

Fire fighting robot remotely operatedMohit Keshav

This document is a project report on a remotely operated firefighting robot. It describes a robot that is loaded with a water tank and pump, and can be controlled wirelessly using an RF transmitter to move in different directions and throw water. The robot uses an 8051 microcontroller and motor driver IC to control three motors - two for movement and one for positioning the robot's arm. The RF transmitter acts as a remote control to send commands to the receiver up to 200 meters away. The project aims to develop a remotely controlled robotic vehicle for firefighting applications.

Robots & SustainabilityJun Takamatsu

20161006 rsp2016 ohkawa-presenTakeshi Ohkawa

The document proposes a method for exploring hardware/software architectures for intelligent robot systems using ROS-compliant FPGA components. It presents a case study of distributing the processing of visual SLAM between a robot and cloud. By partitioning the SLAM tasks and offloading feature extraction to an FPGA component, the proposed architecture reduces the robot's processing time and communication bandwidth requirements compared to an all-software approach. This rapid prototyping method allows exploring different functional partitions and hardware/software mappings at the model level.

Robotic Harvesting of Fruiting Vegetables, ＾Acceleration by Simulation￣Redmond R. Shamshiri

Robotic Harvesting of Fruiting Vegetables, ＾Acceleration by Simulation￣ Presented at the Acceleration Workshop Robotics & Crop Sensing in Greenhouses, 11-12 September 2017. Delf University of Technology, The Netherlands Robotic Harvesting with NOVABOT innovative manipulator https://youtu.be/R38IoVcOVt0 Robotic Harvesting with multiple SCARA manipulators https://youtu.be/TLLW3S-55ls Robotic Harvesting with Array of Linear Actuators https://youtu.be/iFu7FAxLvmg Robotic Harvesting with fanuc lr mate 200id (Visual Servo Control in V-REP, ROS, MATLAB) https://youtu.be/BwRBUeB812s Robotic Harvesting, Simulation of Environment and Fruit/Plant Scan https://youtu.be/XD3J7b0cDGM Advanced Visual Servo Control in V-REP for Robotic harvesting of sweet pepper https://youtu.be/VupoirQOL0Y Robotic Harvesting of Sweet Pepper, Ubuntu, V-REP, ROS Environment Setup https://youtu.be/tKagjNQ9FW4 Real-time, robust and rapid red-pepper fruit detection with Matlab https://youtu.be/rFV6Y5ivLF8 Talk https://youtu.be/QZawPeg3wEQ

Microwave_Oven_ControllerSree Nikhilendra Prasad

This presentation discusses techniques for determining the worst case execution time (WCET) of real-time embedded software, including linear programming, integer linear programming, and implicit path enumeration. It presents the system requirements, control flow graph (CDFG), and test cases for a microwave oven controller. Techniques like mixed-integer linear programming introduce less calculation overhead for calculating WCET compared to other methods.

161117robo_lab

This document provides information about software tools used in a robotics laboratory, including the MORSE simulator, ROS, Blender, Python, and the Protege ontology editor. It describes how to set up and configure these tools, edit simulation scenarios in MORSE, troubleshoot ROS package paths in Python, and access example ontologies in Protege. Setup instructions are provided for Ubuntu, ROS Kinetic, Blender, Python, and downloading and running Protege.

酷永赫粥の�I尖をソフトウェアコンポ�`ネント晒する譜柴ツ�`ル界檎艶遺看馨沿の互字嬬晒の�別�Kazushi Yamashina

This document discusses using cReComp to develop ROS-compliant FPGA components. cReComp is a tool that takes specifications written in scrp and generates FPGA IP cores and C++ driver code. An example is presented where cReComp is used to generate a FIR filter component from a scrp specification. The component communicates with ROS using topics and processes data in real-time on the FPGA to provide latency of less than 1ms. Details are provided on the component architecture generated by cReComp and how it integrates FPGA hardware acceleration with the ROS framework.

Yokogawa in the Water Industry | VigilantPlantYokogawa

CPP Robosub 2014 - White PaperJosh Chrisler

This document describes the Cal Poly Pomona Robosub team's entry in the 2014 Robosub competition. It discusses the team's goals of competing on a $3,500 budget and leaving documentation to help future teams. The team designed an autonomous underwater vehicle (AUV) with a modular aluminum frame, waterproofed electronics, and cameras/sensors interfaced to an onboard computer. The AUV is controlled through PID and fuzzy logic to complete tasks like navigating through an orange pole gate using color/object recognition from camera images. The team aims to place well among first year teams and establish a base for continued participation.

Report on Pick and Place Line following RobotPradeep Yadav

Pick and place Line following robot reportPradeep Yadav

170111 寄セ?ミ2robo_lab

161110robo_lab

160824robo_lab

This document discusses robotics research being conducted at the Robotics Laboratory of Wakayama University Graduate School of System Engineering. The laboratory is using a Leap Motion, Kinect, robot hand, and JETSON TK1 with soracom internet access to conduct research. References are provided relating to robot service initiatives, grasping techniques, and object discovery in 3D scenes via shape analysis.

160427 寄セ?ミ1robo_lab

160713robo_lab

２０１６或界フ?レセ?ンテ�`ションrobo_lab

160717 oc�k燕robo_lab

オ�`フ?ンキャンハ?ススライト?2017robo_lab

More Related Content

Similar to 170111 寄セ?ミ2 (14)

161201robo_lab

RAIOT- Robotics Automation & Internet of Things Lab ReportVishal Aditya

A presentation on obstacle avoiding robotkantankit4

Fire fighting robot remotely operatedMohit Keshav

Robots & SustainabilityJun Takamatsu

20161006 rsp2016 ohkawa-presenTakeshi Ohkawa

Robotic Harvesting of Fruiting Vegetables, ＾Acceleration by Simulation￣Redmond R. Shamshiri

Microwave_Oven_ControllerSree Nikhilendra Prasad

161117robo_lab

酷永赫粥の�I尖をソフトウェアコンポ�`ネント晒する譜柴ツ�`ル界檎艶遺看馨沿の互字嬬晒の�別�Kazushi Yamashina

Yokogawa in the Water Industry | VigilantPlantYokogawa

CPP Robosub 2014 - White PaperJosh Chrisler

Report on Pick and Place Line following RobotPradeep Yadav

Pick and place Line following robot reportPradeep Yadav

161201robo_lab

RAIOT- Robotics Automation & Internet of Things Lab ReportVishal Aditya

A presentation on obstacle avoiding robotkantankit4

Fire fighting robot remotely operatedMohit Keshav

Robots & SustainabilityJun Takamatsu

20161006 rsp2016 ohkawa-presenTakeshi Ohkawa

Robotic Harvesting of Fruiting Vegetables, ＾Acceleration by Simulation￣Redmond R. Shamshiri

Microwave_Oven_ControllerSree Nikhilendra Prasad

161117robo_lab

酷永赫粥の�I尖をソフトウェアコンポ�`ネント晒する譜柴ツ�`ル界檎艶遺看馨沿の互字嬬晒の�別�Kazushi Yamashina

Yokogawa in the Water Industry | VigilantPlantYokogawa

CPP Robosub 2014 - White PaperJosh Chrisler

Report on Pick and Place Line following RobotPradeep Yadav

Pick and place Line following robot reportPradeep Yadav

More from robo_lab (20)

170111 寄セ?ミ2robo_lab

161110robo_lab

160824robo_lab

160427 寄セ?ミ1robo_lab

160713robo_lab

２０１６或界フ?レセ?ンテ�`ションrobo_lab

160717 oc�k燕robo_lab

オ�`フ?ンキャンハ?ススライト?2017robo_lab

或界篋�xrobo_lab

160717 ocホ?スタ�`robo_lab

20160427robo_lab

20160518robo_lab

20160523態讐robo_lab

20160615robo_lab

20160627robo_lab

160713robo_lab

The document summarizes a research paper titled "Object Discovery in 3D scenes via Shape Analysis" presented at the International Conference on Robotics and Automation (ICRA) in 2013. The paper presents an algorithm that takes 3D meshes of indoor environments as input and ranks segments as potential object candidates based on intrinsic shape measures like compactness, symmetry, and smoothness. It evaluates the approach on a dataset of 58 indoor scenes collected with Kinect Fusion, achieving an average precision of 0.92 in detecting objects.

20160713robo_lab

160713 b4hachikirobo_lab

序�単┯�0615robo_lab

序�単┯�0601robo_lab

170111 寄セ?ミ2robo_lab

161110robo_lab

160824robo_lab

160427 寄セ?ミ1robo_lab

160713robo_lab

２０１６或界フ?レセ?ンテ�`ションrobo_lab

160717 oc�k燕robo_lab

オ�`フ?ンキャンハ?ススライト?2017robo_lab

或界篋�xrobo_lab

160717 ocホ?スタ�`robo_lab

20160427robo_lab

20160518robo_lab

20160523態讐robo_lab

20160615robo_lab

20160627robo_lab

160713robo_lab

20160713robo_lab

160713 b4hachikirobo_lab

序�単┯�0615robo_lab

序�単┯�0601robo_lab

Recently uploaded (20)

Cyber Security_ Protecting the Digital World.pptxHarshith A S

decarbonization steel industry rev1.pptxgonzalezolabarriaped

Air pollution is contamination of the indoor or outdoor environment by any ch...dhanashree78

Air pollution is contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics of the atmosphere. Household combustion devices, motor vehicles, industrial facilities and forest fires are common sources of air pollution. Pollutants of major public health concern include particulate matter, carbon monoxide, ozone, nitrogen dioxide and sulfur dioxide. Outdoor and indoor air pollution cause respiratory and other diseases and are important sources of morbidity and mortality. WHO data show that almost all of the global population (99%) breathe air that exceeds WHO guideline limits and contains high levels of pollutants, with low- and middle-income countries suffering from the highest exposures. Air quality is closely linked to the earth¨s climate and ecosystems globally. Many of the drivers of air pollution (i.e. combustion of fossil fuels) are also sources of greenhouse gas emissions. Policies to reduce air pollution, therefore, offer a win-win strategy for both climate and health, lowering the burden of disease attributable to air pollution, as well as contributing to the near- and long-term mitigation of climate change.

Water Industry Process Automation & Control Monthly - March 2025.pdfWater Industry Process Automation & Control

Welcome to the March 2025 issue of WIPAC Monthly the magazine brought to you by the LinkedIn Group WIPAC Monthly. In this month's edition, on top of the month's news from the water industry we cover subjects from the intelligent use of wastewater networks, the use of machine learning in water quality as well as how, we as an industry, need to develop the skills base in developing areas such as Machine Learning and Artificial Intelligence. Enjoy the latest edition

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptxmeneememoo

How to Make an RFID Door Lock System using ArduinoCircuitDigest

G8 mini project for alcohol detection and engine lock system with GPS tracki...sahillanjewar294

IPC-9716_2024 Requirements for Automated Optical Inspection (AOI) Process Con...ssuserd9338b

Power Point Presentation for Electrical Engineering 3-phase.pptAniket_1415

Integration of Additive Manufacturing (AM) with IoT : A Smart Manufacturing A...ASHISHDESAI85

Combining 3D printing with Internet of Things (IoT) enables the creation of smart, connected, and customizable objects that can monitor, control, and optimize their performance, potentially revolutionizing various industries. oT-enabled 3D printers can use sensors to monitor the quality of prints during the printing process. If any defects or deviations from the desired specifications are detected, the printer can adjust its parameters in real time to ensure that the final product meets the required standards.

Name.docxVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVMerijimArsedelPalmad1

GREEN BULIDING PPT FOR THE REFRENACE.PPTkamalkeerthan61

TM-ASP-101-RF_Air Press manual crimping machine.pdfChungLe60

CONTRACTOR ALL RISK INSURANCESAR (1).pptsuaktonny

Introduction to Safety, Health & Environmentssuserc606c7

Equipment for Gas Metal Arc Welding ProcessAhmadKamil87

Engineering at Lovely Professional University (LPU).pdfSona

How to Build a Maze Solving Robot Using ArduinoCircuitDigest

Turbocor Product and Technology Review.pdfTotok Sulistiyanto

Structural QA/QC Inspection in KRP 401600 | Copper Processing Plant-3 (MOF-3)...slayshadow705

This presentation provides an in-depth analysis of structural quality control in the KRP 401600 section of the Copper Processing Plant-3 (MOF-3) in Uzbekistan. As a Structural QA/QC Inspector, I have identified critical welding defects, alignment issues, bolting problems, and joint fit-up concerns. Key topics covered: ? Common Structural Defects �C Welding porosity, misalignment, bolting errors, and more. ? Root Cause Analysis �C Understanding why these defects occur. ? Corrective & Preventive Actions �C Effective solutions to improve quality. ? Team Responsibilities �C Roles of supervisors, welders, fitters, and QC inspectors. ? Inspection & Quality Control Enhancements �C Advanced techniques for defect detection. ? Applicable Standards: GOST, KMK, SNK �C Ensuring compliance with international quality benchmarks. ? This presentation is a must-watch for: ? QA/QC Inspectors, Structural Engineers, Welding Inspectors, and Project Managers in the construction & oil & gas industries. ? Professionals looking to improve quality control processes in large-scale industrial projects. ? Download & share your thoughts! Let's discuss best practices for enhancing structural integrity in industrial projects. Categories: Engineering Construction Quality Control Welding Inspection Project Management Tags: #QAQC #StructuralInspection #WeldingDefects #BoltingIssues #ConstructionQuality #Engineering #GOSTStandards #WeldingInspection #QualityControl #ProjectManagement #MOF3 #CopperProcessing #StructuralEngineering #NDT #OilAndGas

Cyber Security_ Protecting the Digital World.pptxHarshith A S

decarbonization steel industry rev1.pptxgonzalezolabarriaped

Air pollution is contamination of the indoor or outdoor environment by any ch...dhanashree78

Water Industry Process Automation & Control Monthly - March 2025.pdfWater Industry Process Automation & Control

GROUP-3-GRID-CODE-AND-DISTRIBUTION-CODE.pptxmeneememoo

How to Make an RFID Door Lock System using ArduinoCircuitDigest

G8 mini project for alcohol detection and engine lock system with GPS tracki...sahillanjewar294

IPC-9716_2024 Requirements for Automated Optical Inspection (AOI) Process Con...ssuserd9338b

Power Point Presentation for Electrical Engineering 3-phase.pptAniket_1415

Integration of Additive Manufacturing (AM) with IoT : A Smart Manufacturing A...ASHISHDESAI85

Name.docxVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVMerijimArsedelPalmad1

GREEN BULIDING PPT FOR THE REFRENACE.PPTkamalkeerthan61

TM-ASP-101-RF_Air Press manual crimping machine.pdfChungLe60

CONTRACTOR ALL RISK INSURANCESAR (1).pptsuaktonny

Introduction to Safety, Health & Environmentssuserc606c7

Equipment for Gas Metal Arc Welding ProcessAhmadKamil87

Engineering at Lovely Professional University (LPU).pdfSona

How to Build a Maze Solving Robot Using ArduinoCircuitDigest

Turbocor Product and Technology Review.pdfTotok Sulistiyanto

Structural QA/QC Inspection in KRP 401600 | Copper Processing Plant-3 (MOF-3)...slayshadow705

170111 寄セ?ミ2

1. M1 ? 2017/1/11 A204

2. Robotics Laboratory 2 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? ?

3. Robotics Laboratory 3 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? DL ? ? ROS/MORSE ? ? ? FA https://www.openrobots.org/morse/doc/stable/user/robots/pr2.html

4. ＾￣ FUJITSU, Vol.67, No.3, pp.39-44 2016 Robotics Laboratory 4 Wakayama University Graduate School of System Engineering Robotics Laboratory

5. ? ? ? ? ? ? RTM ROS Robotics Laboratory 5 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ?

6. ? ? ? ? ☆ : 1 1 Robotics Laboratory 6 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ?

7. Robotics Laboratory 7 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? ? ? ? 1. ? 2. ? 3. ?

8. Robotics Laboratory 8 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? ? ? ? ? ? ? ?

9. Robotics Laboratory 9 Wakayama University Graduate School of System Engineering Robotics Laboratory ? SLIM* ? ? ? ? * SLIM : Standard Language?for ? Industrial Manipulators? (JIS B 8439:1992) ?

10. Robotics Laboratory 10 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? ? ? ? ? ? ? ? SVM ?

11. Robotics Laboratory 11 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? ? ?

12. Robotics Laboratory 12 Wakayama University Graduate School of System Engineering Robotics Laboratory ＾ ? ￣ , 19 , pp.624-630 2014

13. Robotics Laboratory 13 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? ? ? ?

14. Robotics Laboratory 14 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? TMS ? ? LRF ? IMU ? RFID ? RGBD ? ?

15. Robotics Laboratory 15 Wakayama University Graduate School of System Engineering Robotics Laboratory ROS-TMS ? ROS TMS ? ? LRF RFID ? ? ? ? Choreonoid + graspPlugin ?

16. Robotics Laboratory 16 Wakayama University Graduate School of System Engineering Robotics Laboratory ? SmartPal V Kinect RFID ? LRF RFID RFID ? ? ?

17. Robotics Laboratory 17 Wakayama University Graduate School of System Engineering Robotics Laboratory [Fig.6] LRF ? FSS ? ? [Fig.7] RFID ? ? RFID ? ?

18. Robotics Laboratory 18 Wakayama University Graduate School of System Engineering Robotics Laboratory TMS ROS-TMS ROS-TMS ? ROS ? ? ? ? ?

19. Robotics Laboratory 19 Wakayama University Graduate School of System Engineering Robotics Laboratory ? ? ? DL ? ? ROS/MORSE ? ? FA

20. Robotics Laboratory 20 Wakayama University Graduate School of System Engineering Robotics Laboratory

21. ROS-TMS Robotics Laboratory 21 Wakayama University Graduate School of System Engineering Robotics Laboratory ROS-TMS ? ROS TMS ? ? ? ? ? ? ?

22. ROS-TMS Robotics Laboratory 22 Wakayama University Graduate School of System Engineering Robotics Laboratory

23. Robotics Laboratory 23 Wakayama University Graduate School of System Engineering Robotics Laboratory

24. MORSE Simulator ? 4000 ? 60000 ? telnet MORSE Simulator Robotics Laboratory 24 Wakayama University Graduate School of System Engineering Robotics Laboratory

際際滷

170111 寄セ?ミ2

Recommended

More Related Content

Similar to 170111 寄セ?ミ2 (14)

More from robo_lab (20)

Recently uploaded (20)

170111 寄セ?ミ2