Teemino is an Android ADK compatible board based on Arduino Mega/2560 with USB host. This board is based on Google’s reference design of Android USB accessory.
The board has all the features of an Arduino Mega2560 and also the USB host extensions as defined by Google’s Android ADK design.
The board supports the ADK firmware.
Infos from TheNxtStep (Author: Daniele Benedettelli):
MINDSENSORS has designed this shield that will allow Arduino to replace *ehm* to be integrated into the LEGO MINDSTORMS system.
It will have 4 NXT motor ports, 4 NXT sensor ports and several RC servo motor ports. The NXShield will attach to an Arduino Duemilanove or Uno or similar Arduino clones. (Picture shown here with a Duemilanove)
The programming for the NXShield will be on Arduino, using usual Arduino C/C++ programming environment. There will be only one I2C port, so you can use multiple sensors on the bus only if they have different addresses.
Dieses Manual zeigt wie Apps für das Google Betriebssystem Android programmiert werden können und wie diese u. a. mit
dem LEGO Mindstorms NXT verbunden werden.
Die Entwicklung der Apps erfolgt mit dem App Inventor von Google. Eine Schritt-für-Schritt Anleitung mit vielen Screen-Shots erläutert ausführlich die grafische Programmierung der Android-Apps.
Inhaltsverzeichnis:
Impressum
Vorwort
Allgemeine Information
Warum App Inventor?
Was ist Google App Inventor?
Versuchsaufbau und vorbereitende Arbeiten
Meine Erste App
App zur Steuerung des NXT
Ausblick
Links und Literatur
Link zur Download-Seite: http://roberta-home.de/de/was-bietet-roberta/roberta-reihe/roberta-manual-zum-entwickeln-von-android-apps
The guys at freedroidz developed an android app to remote control the Lego Mindstorms NXT. Here is a Youtube-Video showing the remote control in action:
The required Software is available for download at:
https://wiki.evolvis.org/freedroidz/index.php/Android_Remote_de
Currently I’m participating at the workshop of Safety, Security and Rescue Robots 2010 in Bremen.
The first day is now gone and a lot of interesting talks have been given:
Tetsuya Kinugasa has shown a Flexible Displacement Sensor in his talk of „Measurement of Flexed Posture for Mono-tread Mobile Track Using New Flexible Displacement Sensor„. His group develops and uses this sensor to control the posture of a robot which is a combination of snake, worm and tank.
Jimmy Tran presented his works on „Canine Assisted Robot Deployment for Urban Search and Rescue„. The basic idea is as simple as brilliant, use a equipped dog to find victims and to inform operators about him. So, dogs are well used in rescue and they have a high mobility. They can easily overcome huge rubles and are able to carry video cameras or rescue material. So, his approach is to use the dogs to deploy a small robot next to a victim, which would allow to investigate medical status of the person. The idea is hilarious.
„Development of leg-track hybrid locomotion to traverse loose slopes and irregular terrain“ is so far the most interesting technical approach of this workshop. It shows a way how a tracked like vehicle can be combined with a semi-Walker.
Donny Kurnia Sutantyo presented his work on „Multi-Robot Searching Algorithm Using Levy Flight and Artificial Potential Field„, while Julian de Hoog showed a solution for team exploration in „Dynamic Team Hierarchies in Communication-Limited Multi-Robot Exploration“.
The invited speaker Bernardo Wagner showed the outcomes of his department. The Leibniz University of Hannover has worked intensively in the field of „Perception and Navigation with 3D Laser Range Data in Challenging Environments„.
„Potential Field based Approach for Coordinate Exploration with a Multi-Robot Team“ is topic of Alessandro Renzaglia.
Bin Li showed another nice approach of a shape shifting robot. His robot is able to shape shift it self by rearranging its three motion segments. „Cooperative Reconfiguration between Two Specific Configurations for A Shape-shifting Robot“
Jorge Bruno Silva presented a approach of trajectory planing while respecting time constrains in „Generating Trajectories With Temporal Constraints for an Autonomous Robot“
Noritaka Sato closed the day by presenting novel a HMI approach for teleoperation. Instead of showing only the direct camera image his group uses temporal shifted images to generate an artificial bird eye view, like it is given in computer car games. „Teleoperation System Using Past Image Records Considering Moving Objects“
I am looking forward to listen to the next talks.
A Beginner’s Guide to LEGO MINDSTORMS NXT 2.0
San Francisco, CA, April 22, 2010—The LEGO® MINDSTORMS® NXT 2.0 set brings robot building to a wide range of hobbyists. But the NXT kit doesn’t come with a how-to guide and it only includes building instructions for four robots. Users new to building complex LEGO models or lacking experience with the NXT programming language need guidance to help them reach the next level. The LEGO MINDSTORMS NXT 2.0 Discovery Book is the introductory book that they’ve been waiting for.
In The LEGO MINDSTORMS NXT 2.0 Discovery Book (No Starch Press, May 2010, 320 pp., $29.95, ISBN 9781593272111), readers learn how to harness the capabilities of the NXT 2.0 set to build and program their own robots. Author Laurens Valk begins by walking readers through the set, describing the pieces and explaining how to get started with the software used to program NXT robots. Once readers understand the basics of the NXT programming language, the book’s tutorials show them how to build robots that move, monitor sensors, and use advanced programming techniques like data wires and variables. With crystal clear, step-by-step instructions, readers will find it easy to create working robots in no time. The LEGO MINDSTORMS NXT 2.0 Discovery Book features:
All of the robots in the book require just one NXT 2.0 set to build; there are no extra pieces required.
„The NXT set can be complicated. Sure, you can build some sort of robot, but can you actually make it do anything interesting?“ said No Starch Press founder Bill Pollock. „This is the introductory MINDSTORMS 2.0 book that everyone needs; the one book that will make sure that that pricey MINDSTORMS kit won’t end up gathering dust in a shoebox somewhere.“
Table of Contents
Chapter 1: Collecting the Equipment for Your Robot
Chapter 2: Building Your First Robot
Chapter 3: Creating and Modifying Programs
Chapter 4: Working with Programming Blocks: Move, Sound, and Display
Chapter 5: Waiting, Repeating and Other Programming Techniques
Chapter 6: Understanding Sensors
Chapter 7: Using the Touch, Color, and Rotation Sensors
Chapter 8: Shot-Roller: A Robotic Defense System
Chapter 9: Strider: The Six-Legged Walking Creature
Chapter 10: Using Data Hubs and Data Wires
Chapter 11: Using Data Blocks and Using Data Wires with Loops and Switches
Chapter 12: Using Variables, Constants, and Playing Games on the NXT
Chapter 13: Snatcher: The Autonomous Robotic Arm
Chapter 14: Hybrid Brick Sorter: Sort Bricks by Color and Size
Chapter 15: CCC: The Compact Chimney Climber
Appendix: Transferring Programs to the NXT with USB or Bluetooth
About the Author
Laurens Valk is a member of the MINDSTORMS Community Partners who help test and develop new NXT products. He has been inventing robots with the MINDSTORMS NXT sets since their introduction, and one of his robot designs appears on the NXT 2.0 packaging. Valk is a co-author of LEGO MINDSTORMS NXT One-Kit Wonders (No Starch Press) and a contributor to The NXT Step Blog. He lives in the Netherlands where he teaches robotics.
On of the most common question by handling large data sets is „How to represented the data?“ and of course the answer is versatile. One of the most used solution is a tree like structure, organized by at least one sorting criteria.
KDTree++ is a c++ library which is supporting this feature. KDTrees are allowing to sort data by ‚k‘-Dimensional sorting criteria and the library implements a template based realization. KDTree++ is published under Artistic License 2.0.
Update: I was trying to use KDTree++ in on of our projects on Three-Dimensional perception and Point Clouds analysis. Therefore i was adding roundabout 30.000 Points (x,y,z-coordinates plus some extra informations) into such a tree. The first feeling was quiet positive. It was fast and did not consume that much resources. But by using the search functionality, provided by KDTree++ i was shocked. Every time i was placing a query the memory consumption did rise up dramatically, and even worse, it was staying that high. After investigating the KDTree code i figured out that the library does on each query create a copy of the found items and returns them. Unfortunately those items are never deleted and if i try to deleted them by my self the library produces a segmentation fault. So, summing up i would say that these library is really powerful, but bad documented and seems to have some serious bugs.
Roberta has a new companion, called Jeffrey. Jeffrey is able to find his dockingstation to recharge his battery. Here are some videos of Jeffrey, found on the Roberta Youtube Channel