The purpose of this idea is to control my original robot for tele-operating String-based ROS2 robots with my Xbox Gamepad.
I used to use a keyboard, but I wanted to use a controller for convenience, so I try joy-package.
Until now, I have been using inverse kinematics on ROS2 to calculate the control angle of the serial servo, and sending the calculated Int and Float types as String types to the microcontroller through xrce-micro-dds-Agent for control.
Those reasons are why I cant use teleop-twist-joy package.
I don't want to publish these messages as Twist Messages. I want to send them to a new topic.
What I want to do is as follows.
I want to write a Subscriber to the topic "/joy" and get the data of each Button and each Axes.
Joystick messages to be translated to String messages.
I want to Publish to the topic as (node, std_msgs/msg/String).
so that I can use them in controlling my robot by Xbox Gamepad.
I followed ros document Tutorial : " http://wiki.ros.org/joy/Tutorials/WritingTeleopNode " and I wanted to edit it. But this tutorial shows ROS writing and took information only from the Axis. I want to get from the Buttons too.
Can I have some help or maybe a link to package already done for this type of problems ?
Also, I'm not very good at English, so I'm sorry if my English is difficult to understand or if my sentences are strange.
Related
I am working on a cooking recipe app for google home and I need a way to string several GoogleResponses (SimpleResponse etc..) together without requiring user interaction between them.
I have searched for other answers pertaining to this, and while I have found a few similar questions to mine, the replies tend to be along the lines of "the system was designed for dialogues so what would be the point?".
I fully understand this point of view, however because of the nature and behaviour requirements of the app that I am developing I find myself in need of this particular possibility.
The recipes are divided into steps (revolutionary, I know..) and there is roughly a 1 to 1 correspondence between steps and GoogleResponses.
To give an example of how a typical recipe unfolds it is usually like this (this is a simplification of course):
main content -> question -> main content -> question -> etc..
With each instance of "main content" being a step of the recipe and each "question" requiring user input.
If if was just like this all the time then there would not be a problem, I could just bundle each "main content -> question" section into one GoogleResponse and be done.
However there are often times where the recipe flows more like:
main content -> main content -> main content -> question
With each "main content" being a step in the recipe, it does not make sense in this context to bundle them together into the same response (there is a system for the user to move back and forth between steps).
I was originally using MediaResponses for the "main content" sections as those do not require user input to move onto the next step, but due to various reasons I won't go into here as this is already getting quite long, the project manager has decided that MediaResponses should not be used in this project.
The short answer is the one you already encountered - trying to make conversational actions not-so-conversational doesn't work very well. However, there are a few things you can look into.
Recipe Structured Data
Since you're working on a recipe action, specifically, it may be worthwhile to use the standard recipe support that comes with the Assistant.
On the upside - people will be familiar with it, and you don't need to do much code, just provide markup on a webpage.
On the downside - if you have other requirements for how you want the interaction to go, it isn't that flexible. (For example, if you're asking questions at some of the recipe points, or if you want to offer measurement adjustments based on number of people to serve.)
Misuse the "No Input" event
You can configured dynamic reprompts so you get an event if the user doesn't say anything after a few seconds. If they want to speed a reply, they could ask for the next context specifically, or you can catch the actions_intent_NO_INPUT event in Dialogflow and advance yourself.
There are a few downsides here:
Not all devices support no-input. In particular, for example, mobile devices won't generate this.
This may only be valid for two no-input events in a row. On the third event, the Assistant may automatically close the conversation. (The documentation is unclear on this, and the exact behavior has changed over time.)
Media Response
You're not clear why using Media Response "shouldn't be used", but this is one of the only ways way to trigger an event when speaking is completed.
There are several downsides, however:
There are a number of bugs with Media Response around quitting
On devices with screens, there is a media player. Since the media itself is incidental to what you're doing, having the player doesn't make sense
It isn't supported on all surfaces
Interactive Canvas
A similar approach, however, would be to use the Interactive Canvas. This gives you an HTML page with JavaScript that you control, including being able to generate responses to the server as if the user spoke them (or as if they touched a suggestion chip). You can also listen to events for when the generated speech has finished.
There are, however, a number of downsides which probably prevent you from using this right now:
The biggest is that the Interactive Canvas can only be used for games right now. (But this seems to be a policy decision, rather than a technical one. So perhaps it will be lifted in the future.)
It does not work on smart speakers - only some devices with screens.
Combining the above approaches
One way to get around the device limitations of the Interactive Canvas and the poor visuals that accompany Media Response might be to mix the two. For devices that support IC, use that. If not, try using Media Response. (You may even wish to consider the no-input reprompt for some platforms.)
But this still won't work on all devices, and still has the limitation that Interactive Canvas is only for games right now.
Summary
There is no one, clear, way to handle this... and this isn't a feature they are likely to add given the conversational nature of the platform. However, there may be some workarounds which might work for your scenario.
I am using the Google-actions-sdk v2 and trying to build a gaming application. In the documentation it says conv.ask() is limited to 2 responses per turn. So this basically means I can only show 2 chat bubbles then it will not allow me to display more until after user input. But when I look at some other published applications they have many more then 2 in a row displayed. I can't seem to understand or find any info on how they can get around this limitation. 2 seems a unreasonable limit.
For speech you can merge text lines together and it will sound fine, but presentation on screen is awful without being able to break it down to more responses.
Does anyone out there have any insight on this?
In fact, everything in a single line would sound bad. Why don't you try to separate the necessary texts with the help of the SSML library, I recommend it to you.
You can use the break tag to put a pause between each text.
<speak>
I can pause <break time="3s"/>.
I can pause by second time <break time="3s"/>.
</speak>
Here you have the documentation.
Now if what you want to give is multiple selection options, you can also use the suggestion chip.
https://developers.google.com/actions/assistant/responses#suggestion_chip
I want to create a device like tracker to find objects like keys or any important things. I want to add that sensor to that valuable thing to find where the object i left. I can't use motion sensor, ultrasonic sensor or air proximity because of its check distance form one direction. I need to find out the distance of the object from any direction.
Consider using one of both:
GPS
RDF (Radio Direction Find)
The first is great if you have open sky and client (the looking device) is able to navigate through GPS (thinking in a smartphone).
The second is good for indoor but it can be hard to program and find parts. Look to soloshot. It follows a beacon attached to person of interest. I don´t have their spec but this is a kind of RDF I bet. Airplanes use a avionic based on RDF idea. Read the wikpeadia article on RDF.
Others may come up with other ideas, those where the first that popped in my mind.
my graduate project is about Smart Attendance System for University using RFID.
What if one student have multiple cards (cheating) and he want to attend his friend as well? The situation here my system will not understand the human adulteration and it will attend the detected RFID Tags by the reader and the result is it will attend both students and it will store them in the database.
I am facing this problem from begging and it is a huge glitch in my system.
I need a solution or any idea for this problem and it can be implemented in the code or in the real live to identify the humans.
There are a few ways you could do this depending upon your dedication, the exact tech available to you, and the consistency of the environment you are working with. Here are the first two that come to mind:
1) Create a grid of reader antennae on the ceiling of your room and use signal response times to the three nearest readers to get a decent level of confidence as to where the student tag is. If two tags register as being too close, display the associated names for the professor to call out and confirm presence. This solution will be highly dependent upon the precision of your equipment and stability of temperature/humidity in the room (and possibly other things like liquid and metal presence).
2) Similar to the first solution, but a little different. Some readers and tags (Impinj R2000 and Indy Readers, Impinj Monza 5+ for sure, maybe others aswell) have the ability to report a response time and a phase angle associated with the signal received from an interrogated tag. Using a set up similar to the first, you can get a much higher level of reliability and precision if you use this method.
Your software could randomly pick a few names of attending people, so that the professor can ask them to identify themselves. This will not eliminate the possibility of cheating, but increase the risk of beeing caught.
Other idea: count the number of attendiees (either by the prof or by camera + SW) and compare that to the number of RfID tags visible.
There is no solution for this RFID limitation.
But if you could then you can use Biometric(fingerprint) recognition facility with RFID card. With this in your system you have to:
Integrate biometric scanner with your RFID reader
Store biometric data in your card
and while making attendance :
Read UID
Scan biometric by student
Match scanned biometric with your stored biometric(in the card :
step 2)
Make attendance (present if biometric matched, absent if no match)
Well, We all have that glitch, and you can do nothing about it, but with the help of a camera system, i think it would minimise this glitch.
why use a camera system and not a biometric fingerprint system? lets re-phrase the question, why use RFID if there is biometric fingerprint system ? ;)
what is ideal to use, is an RFID middleware that handle the tag reading.
once the reader detects a tag, the middleware simply call the security camera system and request for a snapshot, and store it in the db. I'm using an RFID middleware called Envoy.
I have an app that extracts information from incoming messages. The messages all contain the same information, but they have different forms depending on the source that sent them.
Example:
Message from source A :
A: You spent $50.00 at Macy's on 2/20/12
Message from source B :
Purchase, $50.00, Macy's, 2Feb2012, Balance $5000.00
Every message from a single source has the same form though. So at the moment, I'm doing it by writing a set of regular expressions to first identify which message I'm trying to decode (i.e. what source it came from so I know what the form of the message is), and then extracting the necessary information from the message (in the above example, I want to know the transaction amount, the store where the transaction happened, and the date). If I discover a new source for a message, or a source changes the format of their message (doesn't happen very often, but could happen), I need to manually write the regular expressions for that message. I'm sure however that I could automate this using some kind of machine learning technique. I just don't know much about machine learning, and I don't know where to even start looking for a technique that would apply to my problem. I would like someone to just point me in the right direction on where to start reading.
In order to detect and label amounts, dates, person names and similar information you can use a technique called Named Entity Recognition. The Stanford Named Entity Recognizer comes with pretrained, ready to use models.
You also use whatever labeled data you have generated so far to learn a custom model for your application. The standard techniques used for this purpose are Conditional Random Fields or Sequence Perceptron. There are many toolkits implementing these models, including:
Wapiti - A simple and fast discriminative sequence labelling toolkit.
Sequor - sequence labeler based on Collins's (2002) perceptron.