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Algorithms
Agents can be instructed to perform algorithms either alone or as part of a team. These are initialized using defined Madara variables read by the Controller. Algorithms are defined by a command and some variable number of parameters. Two basic types of algorithms will be discussed, Area Coverage and Formation. The command keys are all prefixed by "device.{.id}.", so for agent 1 the keys would be "device.1.command".
During algorithm initialization, a set of algorithm status variables are created in the knowledge base. These are of
the form device.{.id}.algorithm.<algorithm_name>. {.id} is the id of the device running the algorithm.
<algorithm_name> is the algorithm that the device is executing. The <algorithm_name> is the all lower case version
of the name of each algorithm. The <algorithm_name> for area coverage algorithms is listed next to each algorithms
name and is a shortened form of the full algorithm.
Area Coverage algorithms instruct a group of drones to surveil a region or search area. The behavior can determined by a random distribution, sensor data from the swarm, or precomputed before beginning the coverage. More information about these algorithms is on the Area Coverage page.
The formation algorithm allows any static formation to be defined and used by a group of agents.
| Key | Value |
|---|---|
| command | "formation" |
| command.0 | lead agent id |
| command.1 | offset |
| command.2 | destination |
| command.3 | member list |
The formation algorithm is initialized by the "formation" command and requires four arguments. The first argument is the id of the "lead" agent of the formation. This agent is the common reference point for the next argument.
The second argument is the relative location of this agent in the formation. This parameter is a
double vector of values ( [rho,phi,z] ) in the cylindrical coordinate
system with the location of the lead agent as the origin. rho is the planar distance
from the lead. phi is the angular offset in radians from forward of the lead agent with
positive phi being to the right and negative phi to the left. z is the altitude offset. For
example [3,1.57,4] would be the position three meters to the right of and four meters above the
lead agent. The lead agent is at [0,0,0], but it will ignore this value regardless. If z is
missing, then it is defaulted to 0.
The third argument is the destination of the formation. This allows formation members to determine the forward direction of the lead agent and thus their expected absolute position. It is assumed the formation will stay at the same altitude at which it starts. This is also a double vector.
The fourth argument is the list of agents involved in the formation as an integer vector. For example, if agents 4, 2, 6, 3, and 8 are involved in the formation, then the parameter should be [4,2,6,3,8].
The follow algorithm has an agent follow another agent with a known position.
| Key | Value |
|---|---|
| command | "follow" |
| command.0 | target id |
| command.1 | delay |
The follow algorithm is called with the "follow" command. It takes two arguments. The first is the
id of the target to follow. This is used to key on the device.{target}.location variable in the
knowledge base. The second argument is the delay. The agent will be delay timesteps behind the
target agent.
The move algorithm has an agent move to a new location.
| Key | Value |
|---|---|
| command | "move" |
| command.0 | location |
The wait algorithm does nothing, but returns a FINISHED status after a period of time has passed.
| Key | Value |
|---|---|
| command | "wait" |
| command.0 | time in seconds |
The Executive algorithm is a queue of other algorithms to run.
| Key | Value |
|---|---|
| command | "executive" |
| command.0 | algorithm 0 |
| command.1 | args for algorithm 0 |
| ... | ... |
| command.2n - 2 | algorithm n |
| command.2n - 1 | args for algorithm n |
The Executive algorithm is a way to set a series of commands for an agent to execute. This can be useful if agents need to travel outside of network communications range and a single algorithm will not accomplish all the work that the agent needs to do while disconnected. Below is an example.
| Key | Value |
|---|---|
| command | "executive" |
| command.0 | "move" |
| command.1 | "move_args_0" |
| command.2 | "wait" |
| command.3 | "wait_args" |
| command.4 | "urec" |
| command.5 | "urec_args_0" |
| command.6 | "wait" |
| command.7 | "wait_args" |
| command.8 | "move" |
| command.9 | "move_args_1" |
The even numbered command args (0,2,4,...) are the algorithms to run while the odd numbered command args (1,3,5,...) are the arguments to those algorithms. In this case "move_args_0", "wait_args", "urec_args_0", and "move_args_1" need to be populated.
| Key | Value |
|---|---|
| move_args_0.0 | "5" |
| move_args_0.1 | "5" |
| wait_args.0 | "10" |
| urec_args_0.0 | "region.0" |
| move_args_1.0 | "0" |
| move_args_1.1 | "0" |
These values will have the agent move to location (5,5), wait 10 seconds, perform a Uniform Random Edge Coverage over region.0, wait 10 seconds, and then move to location (0,0).