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ease:workshop [2020/07/15 22:50] – [Solution suggestions] Added solutions and screenshots hawkinease:workshop [2020/09/01 09:55] (current) – added video to intriduction hawkin
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 ==== Abstract ==== ==== Abstract ====
 In order to enable robots to perform every day activities with ease, they need to know when to do what. And who could be a better teacher then the human who wants the robots to perform these tasks? But instead of having us humans explain to the robots what to do, it is easier to just show them in a Virtual Reality environment, since the VR world can easily be adapted to whichever tasks we want to teach. In order to enable robots to perform every day activities with ease, they need to know when to do what. And who could be a better teacher then the human who wants the robots to perform these tasks? But instead of having us humans explain to the robots what to do, it is easier to just show them in a Virtual Reality environment, since the VR world can easily be adapted to whichever tasks we want to teach.
 +
 +In the following video we can see how a human performs everyday activities within the VR environment.
 +
 +<html>
 +<div style="padding:56.25% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/199633754" style="position:absolute;top:0;left:0;width:100%;height:100%;" frameborder="0" allow="autoplay; fullscreen" allowfullscreen></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>
 +<p><a href="https://vimeo.com/199633754">RobCoG</a> from <a href="https://vimeo.com/andreihaidu">Andrei Haidu</a> on <a href="https://vimeo.com">Vimeo</a>.</p>
 +</html>
 +
 Before we can teach the robots though, we have to understand what kind of data is being recorded and how we can access and inspect it, before we decide which parts of it to pass on to the robots.  Before we can teach the robots though, we have to understand what kind of data is being recorded and how we can access and inspect it, before we decide which parts of it to pass on to the robots. 
 This tutorial will aim at teaching how to interact with episodic memories and inspect the data stored within using [[http://data.open-ease.org/user/sign-in|Open Ease]] and [[https://www.swi-prolog.org/|Prolog]] queries. This tutorial will aim at teaching how to interact with episodic memories and inspect the data stored within using [[http://data.open-ease.org/user/sign-in|Open Ease]] and [[https://www.swi-prolog.org/|Prolog]] queries.
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 ==== Introduction ==== ==== Introduction ====
-We can record everything the human does in a Virtual Reality environment fairly precisely. The position of the head of the human can be tracked by tracking the headset itself, while the position of the hands can be mapped to the poistion of the joysticks. Every interaction between the hands of the human with the virtual environment is recorded. We can replay these recordings (episodes) and inspect them, learning from them how a human does certain every day activities. Why do we do certain tasks in a specific order? (E.g. in a table setting scenario, most people would put the plate down first and then get the cutlery.) How do we place objects? What orientation of objects do we tend to prefer?  +We can record everything the human does in a Virtual Reality environment fairly precisely. The position of the head of the human can be tracked by tracking the headset itself, while the position of the hands can be mapped to the position of the joysticks.  
-All of these things are small subconscious decisions we are not necessarily aware of, since we are just used to do things a certain way. How should a robot know them? This is where episodic memories come in. We can use the recorded data from Virtual Reality to teach robots to do every day activities without having to hard code every small little detail into the program of the robot (at least that's the goal). Before we can get there though, we need to understand and see how the data is stored, what we can learn from it and what information can be obtained in the first place.+ 
 +Every interaction between the hands of the human with the virtual environment is recorded. We can replay these recordings (episodes) and inspect them, learning from them how a human does a certain everyday activity. Why do we do tasks in a specific order? (For instance, in a table setting scenario most people would put the plate down first and then get the cutlery.) How do we place objects? What orientation of objects do we tend to prefer?  
 + 
 + 
 +All of these things are small subconscious decisions we are not necessarily aware of since we are just used to do things a certain way. How should a robot know them? This is where episodic memories come in. We can use the recorded data from Virtual Reality to teach robots to do everyday activities without having to hard code every small little detail into the program of the robot (at least that's the goal). Before we can get there though, we need to understand and see how the data is stored, what we can learn from it, and what information can be obtained in the first place. 
  
 ==== Tutorials ==== ==== Tutorials ====
 == Setup the Tutorial Environment == == Setup the Tutorial Environment ==
-Go to the website [[http://data.open-ease.org]], preferably using Mozilla Firefox or Chrome (other browsers could work as well but have not been tested). You do not need to log in into the website to complete this tutorial. In the upper right corner, select ''Experiment Selection'' and from the appearing drop down menu select ''VR Breakfast (EASE) Milestone''. +Go to the website [[http://data.open-ease.org]], preferably using Mozilla Firefox or Chrome (other browsers could work as well but have not been tested). You do not need to log in into the website to complete this tutorial. In the upper right corner, select ''Experiment Selection'' and from the appearing drop-down menu select ''VR Breakfast (EASE) Milestone''. 
  
-Click on ''Teaching'' in the menu bar, ''Tutorials'' and in the tutorials overview select ''Fall School VR Tutorials''. Read and do this overview Tutorial which should look like this:+Click on ''Teaching'' in the menu bar, ''Tutorials'', and in the tutorials overview select ''Fall School VR Tutorials''. Read and do this overview Tutorial which should look like this:
  
 {{ :ease:oe_introduction.jpg |}} {{ :ease:oe_introduction.jpg |}}
  
-The tutorial will explain a few basics, as well as describe the goals of the following tasks. If you want to get more familiar with OpenEase first and this is your first encounter with OpenEase, KnowRob and Prolog, it is advisable to also read and do the other tutorials available in the tutorial overview.+The tutorial will explain a few basics, as well as describe the goals of the following tasks. If you want to get more familiar with OpenEase first and this is your first encounter with OpenEase, KnowRob, and Prolog, it is advisable to also read and do the other tutorials available in the tutorial overview.
  
 The following description comments on the build-in ''Virtual Reality NEEMs'' Tutorial within OpenEase, by trying to explain in more detail what certain queries do and why they are used the way they are. You can of course try to complete the Tutorial on your own without the information which is provided here. It's up to you.  The following description comments on the build-in ''Virtual Reality NEEMs'' Tutorial within OpenEase, by trying to explain in more detail what certain queries do and why they are used the way they are. You can of course try to complete the Tutorial on your own without the information which is provided here. It's up to you. 
  
-In order to be able to visualize what happened within an episode, we first need to load the environment in which that episode took place, as well as the episode in question. In short: we need to tell OpenEase what to load from the database and that we want the result to be visualized. In order to achieve this, select the ''Initialization'' query from the suggested queries in the bottom left corner. The entire query will then appear in the query editor, so that we can inspect which individual queries are called and edit them if needed be. In this case we can just keep the query as-is and submit it with the little button labled with a questionmark. +In order to be able to visualize what happened within an episode, we first need to load the environment in which that episode took place, as well as the episode in question. In short: we need to tell OpenEase what to load from the database and that we want the result to be visualized. In order to achieve this, select the ''Initialization'' query from the suggested queries in the bottom left corner. The entire query will then appear in the query editor so that we can inspect which individual queries are called and edit them if needed be. In this case, we can just keep the query as-is and submit it with the little button labeled with a question mark. 
 Now the environment, in this case a kitchen, will be loaded in the visualization overview panel. This might take some time to load, it can even take up several minutes, so don't worry if it is slow or some objects just appear as black cubes. This is normal.  Now the environment, in this case a kitchen, will be loaded in the visualization overview panel. This might take some time to load, it can even take up several minutes, so don't worry if it is slow or some objects just appear as black cubes. This is normal. 
  
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 Now these are a few queries chained together by a '','' which acts as an ''and'' in prolog. The fullstop ''.'' at the end is also very important. It signals the end of the query and you might get an error message if you forget to add it.  Now these are a few queries chained together by a '','' which acts as an ''and'' in prolog. The fullstop ''.'' at the end is also very important. It signals the end of the query and you might get an error message if you forget to add it. 
  
-''owl_parse'' parses the path of the EventData.owl file and the SemanticMap so what OpenEase knows which episode to load. The EventData contains every event that traspired in the episode. Every action like pick and place etc. is recorded as an Event in the EventData. The SemanticMap contains the initial state of the world, including which object is where, and how the world is set up. Aka if you do experiments in a kitchen, it will describe where all the kitchen Furniture and objects are, where the meshes are located etc. With these queries this information gets loaded into OpenEase.+''owl_parse'' parses the path of the EventData.owl file and the SemanticMap so what OpenEase knows which episode to load. The EventData contains every event that happened in the episode. Every action like pick and place etc. is recorded as an Event in the EventData. The SemanticMap contains the initial state of the world, including which object is where, and how the world is set up. Aka if you do experiments in a kitchen, it will describe where all the kitchen Furniture and objects are, where the meshes are located etc. With these queries, this information gets loaded into OpenEase.
  
-''connect_to_db'' connects to the MongoDB database which contains all the poses of the objects during the Events. The poses are mapped  to timestamps. +''connect_to_db'' connects to the MongoDB database which contains all the poses of the objects during the Events. The poses are mapped to timestamps. 
  
 ''sem_map_inst'' asks for the current instance of a SemanticMap. ''sem_map_inst'' asks for the current instance of a SemanticMap.
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 ''show'' visualizes the SemanticMap in the visualization pane. ''show'' visualizes the SemanticMap in the visualization pane.
  
-Note how after executing these queries you also get their results in the result pane above the question answering pane. In this case, we only had one varibale, namely ''MapInst'' (Everything starting with a capital letter is a variable for Prolog). This variable now contains the map instance of the semantic map that we have loaded and represents it like this: +Note how after executing these queries you also get their results in the result pane above the question answering pane. In this case, we only had one variable, namely ''MapInst'' (Everything starting with a capital letter is a variable for Prolog). This variable now contains the map instance of the semantic map that we have loaded and represented it like this: 
 <code prolog> <code prolog>
 MapInst = http://knowrob.org/kb/u_map.owl#SemanticEnvironmentMap_iW6S MapInst = http://knowrob.org/kb/u_map.owl#SemanticEnvironmentMap_iW6S
 </code> </code>
-Whenever we use variables, it can always be the case that there are multiple solutions to one question. If you want to know if this is the only solution or if there are more, click on the little arrow button right next to the questionmark button. There are solutions as long as you are able to click the button, and as long as you do not get a ''true'' or ''false'' statement in the result pane.+Whenever we use variables, it can always be the case that there are multiple solutions to one question. If you want to know if this is the only solution or if there are more, click on the little arrow button right next to the question mark button. There are solutions as long as you are able to click the button, and as long as you do not get a ''true'' or ''false'' statement in the result pane.
  
 ==== Tasks and Exercises ==== ==== Tasks and Exercises ====
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 === Task Questions === === Task Questions ===
 Task 1: Which type of objects are brought by the demonstrators?  Task 1: Which type of objects are brought by the demonstrators? 
 +
 Task 2: What are these objects' initial poses? Task 2: What are these objects' initial poses?
 +
 Task 3: What are their final poses? Task 3: What are their final poses?
 +
 Task 4: Highlight the human when he starts to grasp an object Task 4: Highlight the human when he starts to grasp an object
  
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 </code> </code>
  
-Result: +**Result:** 
 <code prolog> <code prolog>
 ObjShortName = KoellnMuesliCranberry_2pcO ObjShortName = KoellnMuesliCranberry_2pcO
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 {{ :ease:solution_2.png |}} {{ :ease:solution_2.png |}}
- 
 == Task 3: What are their final poses? == == Task 3: What are their final poses? ==
 Idea: Same as the above except for the timestamp change from start to end. Idea: Same as the above except for the timestamp change from start to end.
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 </code> </code>
  
-Result:+**Result:**
 <code prolog> <code prolog>
 ObjShortName = KoellnMuesliCranberry_2pcO ObjShortName = KoellnMuesliCranberry_2pcO
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 </code> </code>
  
-Result: +**Result:** 
 <code prolog> <code prolog>
 EpInst = http://knowrob.org/kb/unreal_log.owl#UnrealExperiment_Hnkn EpInst = http://knowrob.org/kb/unreal_log.owl#UnrealExperiment_Hnkn
ease/workshop.1594853455.txt.gz · Last modified: 2020/07/15 22:50 by hawkin
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