Swarm Robot Project Simulator - Revision history

NealEhardt: /* Versions */

2009-12-01T04:22:17Z

Versions

NealEhardt at 19:52, 17 November 2009

2009-11-17T19:52:22Z

NealEhardt: /* Packet model */

2009-08-27T20:12:59Z

Packet model

Sam Bobb at 19:31, 18 August 2009

2009-08-18T19:31:06Z

NealEhardt at 19:30, 28 May 2009

2009-05-28T19:30:12Z

NealEhardt: /* Data model */

2009-05-28T04:37:48Z

Data model

NealEhardt: /* Time model */

2009-05-27T15:42:28Z

Time model

NealEhardt: /* Consensus Input */

2009-05-25T19:14:38Z

Consensus Input

NealEhardt: /* Getting started */

2009-05-25T19:02:28Z

Getting started

NealEhardt: /* Control structure */

2009-05-25T18:47:38Z

Control structure

@@ Line 2: / Line 2: @@
 =Versions=
-There are now two versions of the simulator that implement different algorithms: formation control and environment sensing.  They both use the same control structure, which this article describes from the perspective of the formation control algorithm.
+There are now two versions of the simulator that implement different algorithms.  They both use the same control structure, which this article outlines in context of the formation control algorithm.
 ==Formation control==
 File: [[Image:Swarm_Robot_Project_Simulator.zip]]
+Here the robots orient themselves so that their moments (quantifiers of the group's shape and position) match a predefined set of goal moments.
 The swarm will start centered around a random point and then converge on the goal moments (shown as the stationary green ellipse).  The user may click a location on the grid to restart the simulation with the robots centered around that point.
@@ Line 12: / Line 14: @@
 File: [[Image:Swarm_Robot_Project_Simulator_environment.zip]]
+Here the robots are placed in an environment with up to 3 variables that are functions of location.  The robots collaboratively model these variables and relocate themselves to get optimal sensor readings.
-The swarm starts clustered at a random location in an environment with randomly chosen parameters.  The agents monitor three variables, displayed as red, green, and blue.  Click on an agent to open a plot of its error (a black field indicates perfect estimate of all colors).  The environment function is defined in ''basefunction.m'' and it can be changed to anything.
+The swarm starts clustered at a random location in an environment with randomly chosen parameters.  The three environment variables are displayed on top of each other as red, green, and blue.  Click on an agent to open a plot of its error (a black field indicates perfect estimate of all colors).  The environment function is defined in ''basefunction.m'' and it can be changed to anything.
+For this application, the agents' states have three extra data fields:
+* '''bots'''
+** '''state'''
+*** '''Y''' information matrix
+*** '''Tau''' information vector
+*** '''sensorR''' sensor covariance
 =Getting started=

@@ Line 1: / Line 1: @@
-The simulator is a part of the [[Swarm Robot Project]] that attempts to model the robots using MATLAB.  It is built around a modular control structure so that it can be easily adapted to run other algorithms.  Features include: asynchronous update cycles, a packet model, lossy communication, and flexible rendering options.
+The simulator is a part of the [[Swarm Robot Project]] that attempts to model the robots using MATLAB.  It is built around a modular control structure so that it can be easily adapted to run other algorithms.  Features include asynchronous update cycles, a packet model, lossy communication, and flexible rendering options.
+=Versions=
+There are now two versions of the simulator that implement different algorithms: formation control and environment sensing.  They both use the same control structure, which this article describes from the perspective of the formation control algorithm.
+==Formation control==
+File: [[Image:Swarm_Robot_Project_Simulator.zip]]
+The swarm will start centered around a random point and then converge on the goal moments (shown as the stationary green ellipse).  The user may click a location on the grid to restart the simulation with the robots centered around that point.
+==Environment sensing==
+File: [[Image:Swarm_Robot_Project_Simulator_environment.zip]]
+The swarm starts clustered at a random location in an environment with randomly chosen parameters.  The agents monitor three variables, displayed as red, green, and blue.  Click on an agent to open a plot of its error (a black field indicates perfect estimate of all colors).  The environment function is defined in ''basefunction.m'' and it can be changed to anything.
 =Getting started=
 To run the simulator:
-# Download the zip file: [[Image:Swarm_Robot_Project_Simulator.zip]]
+# Download one of the zip files above.
 # Extract the ''Simulator'' folder.
 # Open ''simulator.m'' and press Run.
 # When prompted, select "Change Directory".
-==What you're seeing==
+==Code organization==
+Each M-file is a MATLAB function.  The central one is ''simulator.m''.  At the top of ''simulator.m'', you will find some constants (denoted by all-caps) that make it easy to change the performance and rendering of the simulation without having to read into the code.  See the inline comments for details.
-This version implements the formation control algorithm.  The swarm will start centered around a random location and then converge on the goal moments (shown as the stationary green ellipse).  The user may click a location on the grid to restart the simulation with the robots centered around that point.
-==Organization==
-Each M-file is a MATLAB function.  The central one is ''simulator.m''.  At the top of ''simulator.m'', you will find some constants (denoted by all-caps) that give the user a great deal of control over the performance and rendering of the simulation without having to understand the code.  See the inline comments for details.
 =Control structure=

@@ Line 69: / Line 69: @@
 Consensus information is transferred between the e-pucks using wireless communications.  The simulator transfers packets between robots on an asynchronous basis and includes the possibility of packet loss as a function of distance.  Each robot's ''packets'' vector contains the most recently received packet from each of its neighbors.  A robot will transmit its own consensus information just before its control structure is executed.
-Packet loss is modeled by a cumulative Rice function, as advised by [http://www.springerlink.com/content/u34264k58822l872/|The problem of Wi-Fi radio-fading simulation: Solution and applications].  As distance between agents increases, the probability of receiving a packet decreases.
+Packet loss is modeled by a cumulative Rice function, as advised by [http://www.springerlink.com/content/u34264k58822l872/ The problem of Wi-Fi radio-fading simulation: Solution and applications].  As distance between agents increases, the probability of receiving a packet decreases.
 ===Visualizing packet loss===

← Older revision		Revision as of 19:31, 18 August 2009
Line 83:		Line 83:

	Movies are recorded as uncompressed AVIs because MATLAB does a poor job of compression. See [[Swarm Robot Project Documentation#Making Videos with Overlays]].		Movies are recorded as uncompressed AVIs because MATLAB does a poor job of compression. See [[Swarm Robot Project Documentation#Making Videos with Overlays]].

			[[Category:SwarmRobotProject]]

@@ Line 4: / Line 4: @@
 To run the simulator:
 # Download the zip file: [[Image:Swarm_Robot_Project_Simulator.zip]]
-# Extract the Simulator folder.
+# Extract the ''Simulator'' folder.
 # Open ''simulator.m'' and press Run.
 # When prompted, select "Change Directory".
@@ Line 11: / Line 11: @@
 This version implements the formation control algorithm.  The swarm will start centered around a random location and then converge on the goal moments (shown as the stationary green ellipse).  The user may click a location on the grid to restart the simulation with the robots centered around that point.
-==Constants==
+==Organization==
-The constants at the top of the M-file (denoted by all-caps) give the user a great deal of control over the performance and rendering of the simulation without having to understand the code.  See the inline comments for details.
+Each M-file is a MATLAB function.  The central one is ''simulator.m''.  At the top of ''simulator.m'', you will find some constants (denoted by all-caps) that give the user a great deal of control over the performance and rendering of the simulation without having to understand the code.  See the inline comments for details.
-==Files==
-Each file is a MATLAB function.  The central one is ''simulator.m''.  See Control Structure for details about the other ones.
 =Control structure=
@@ Line 24: / Line 21: @@
 ==Blue boxes==
-The blue boxes represent functions that are defined in their own files.  They are the building blocks of the consensus-based swarm model.
+The blue boxes from the flowchart to the right represent functions that are defined in their own files.  They are the building blocks of the consensus-based swarm model.
 ===Plant===
@@ Line 45: / Line 42: @@
 The velocity output from the Controller is put through a collision avoidance algorithm.  It is not shown in the flowchart because the algorithm has access to the positions of all the agents (information not known to any single agent).
-The present algorithm does not work very well.
+Note: the present algorithm does not work very well.
 =Environment=
-The environment encapsulates the control structure, simulating passage of time, motion of the agents, and lossy wireless communication.
+The environment is a set of abstractions that encapsulate the control structure, simulating passage of time, motion of the agents, and lossy wireless communication.
 ==Time model==

@@ Line 56: / Line 56: @@
 ==Data model==
-Since all state data in the simulation can be associated with a robot, the only stored variable is a vector of N robots called ''bots''.  Each bot is individually represented as a structure, with the following fields:
+Since all state data in the simulation can be associated with a robot, the only stored variable is a vector of N robots called ''bots''.  Each bot is individually represented as a struct, with the following fields:
 * '''bots''' vector of N robots
-** '''state''' information the robot knows about itself
+** '''state''' information the agent knows about itself
 *** '''p''' position
 *** '''angle''' rotational orientation
-** '''packets''' vector of N received packets (packet i of bot i is that robot's own estimate and does not age like the rest)
+** '''packets''' vector of N received packets (packet ''i'' of bot ''i'' is that agent's own estimate and always has an age of 0.)
 *** '''age''' timesteps since received
 *** '''v''' PI decision variable
 *** '''w''' PI estimator state
-** '''u''' velocity
+** '''u''' velocity chosen by Controller
 ** '''lastUpdate''' timestep of last update
-** '''waitTime''' timesteps between previous update and next update
+** '''waitTime''' timesteps between last update and next update
 ==Packet model==

@@ Line 51: / Line 51: @@
 ==Time model==
-The simulation advances in ''timesteps''; equally spaced spans of time.  Timesteps are the unit used in specifying the distance between discrete events (ie. updating robot calculations or rendering).
+The simulation advances in ''timesteps''; equally spaced spans of time.  Timesteps are the unit used in specifying the distance between discrete events, such as updating robot calculations or rendering.  Their size (relative to other time-based units) is defined by the constant ''dT''.
 The main loop runs once per timestep.  It updates the plant every timestep and makes calls to time-dependent update functions as needed.

@@ Line 36: / Line 36: @@
 ===Consensus Input===
-Injects the agent's own information into the estimator-communication cycle.
+Injects the agent's own information into the estimator-communication cycle.  In the formation control implementation, this step causes the estimates to follow the agents instead of converging to the starting location.
 ===Controller===

@@ Line 17: / Line 17: @@
 =Control structure=
-[[Image:swarm_simlulator_control_structure.png|300px|right|thumb|Control structure flowchart.  Blue boxes represent functions that are defined in their own files.]]
+[[Image:swarm_simulator_control_structure.png|300px|right|thumb|Control structure flowchart]]
 The control structure represents the decentralized code that runs on the individual e-pucks.  It is written modularly and without extraneous dependencies so it can be readily adapted to other algorithms.
 The whole control structure is called from ''updateBotComputations''.  Information about neighbors flows to and from the consensus estimator via the packet model.
+==Blue boxes==
+The blue boxes represent functions that are defined in their own files.  They are the building blocks of the consensus-based swarm model.
+===Plant===
+The interface between the agent and the environment.  For the formation control implementation, this models an e-puck following a velocity vector.
+===Sensors===
+Consolidates information from the environment into a form readable by Consensus Input and the Controller.
+===Consensus Estimator===
+A discrete-time PI estimator that uses packet structs for its input and output.
+===Consensus Input===
+Injects the agent's own information into the estimator-communication cycle.
+===Controller===
+Uses the agent's sensory and consensus information to select a set of controls, sent to the plant.
 <br clear=all>