pyRobots: a toolkit for robot executive control

As you may well know if you ever tried to use them to implement under-specified tasks, state machines are not the best tool to code robot controllers.

pyRobots provides a set of Python decorators to easily turn standard functions into background tasks which can be cancelled at anytime and to make your controller resource aware (no, a robot can not turn left AND right at the same time).

It also provides a event-based mechanism to monitor specific conditions and asynchronously trigger actions.

It finally provides a library of convenient tools to manage poses in a uniform way (quaternions, Euler angles and 4D matrices, I look at you) and to interface with existing middlewares (ROS, naoqi, aseba...).

Main features

  • Turns any Python function into a background action with the decorator @action.

  • Robot actions are non-blocking by default: they are instanciated as futures (lightweight threads),

  • Actions can be cancelled at any time via signals (the ActionCancelled signal is raised):

    @action
    def safe_walk(robot):
    try:
        robot.walk()
    except ActionCancelled:
        robot.go_back_to_rest_pose()
    
    action = robot.safe_walk()
    time.sleep(1)
    action.cancel()
    
  • Lock specific resources with a simple @lock(...) in front of the actions. When starting, actions will wait for resources to be available if needed:

    L_ARM = Resource()
    R_ARM = Resource()
    ARMS = CompoundResource(L_ARM, R_ARM)
    
    @action
    @lock(ARMS)
    def lift_box(robot):
        #...
    
    @action
    @lock(L_ARM)
    def wave_hand(robot):
        #...
    
    @action
    @lock(L_ARM, wait=False)
    def scratch_head(robot):
        #...
    
    robot.lift_box()
    robot.wave_hand() # waits until lift_box is over
    robot.scratch_head() # skipped if lift_box or
                        # wave_hand are still running
    
  • Supports compound resources (like WHEELS == LEFTWHEEL + RIGHTWHEEL)

  • Create event with robot.whenever(<condition>).do(<action>)

  • Poses are managed explicitely and can easily be transformed from one reference frame to another one (integrates with ROS TF when available).

  • Extensive logging support to debug and replay experiments.

Support for a particular robot only require to subclass GenericRobot for this robot (and, obviously, to code the actions you want your robot to perform).

Code Documentation

The documentation is currently sparse. Please fill bug reports everytime you can not figure out a specific bit.

Main entry points

Minimum Working Example

...that includes the creation of a specific robot

import time
from robots import GenericRobot
from robots.decorators import action, lock
from robots.resources import Resource
from robots.signals import ActionCancelled

# create a 'lockable' resource for our robot
WHEELS = Resource("wheels")

class MyRobot(GenericRobot):

    def __init__(self):
        super(MyRobot, self).__init__()

        # create (and set) one element in the robot's state. Here a bumper.
        self.state.my_bumper = False

        # do whatever other initialization you need :-)

    def send_goal(self, pose):
        # move your robot using your favorite middleware
        print("Starting to move towards %s" % pose)

    def stop(self):
        # stop your robot using your favorite middleware
        print("Motion stopped")

    def whatever_lowlevel_method_you_need(self):
        pass

@lock(WHEELS)
@action
def move_forward(robot):
    """ We write action in a simple imperative, blocking way.
    """

    # the target pose: simply x += 1.0m in the robot's frame. pyRobots
    # will handle the frames transformations as needed.
    target = [1.0, 0., 0., "base_link"]

    try:
        robot.send_goal(target)

        while(robot.pose.distance(robot.pose.myself(), target) > 0.1):
            # robot.sleep is exactly like time.sleep, except it lets the pyrobots
            # signals pass through.
            robot.sleep(0.5)

        print("Motion succeeded")

    except ActionCancelled:
        # if the action is cancelled, clean up your state
        robot.stop()


with MyRobot() as robot:

    # Turn on DEBUG logging.
    # Shortcut for logging.getLogger("robots").setLevel(logging.DEBUG)
    robot.debug()

    robot.whenever("my_bumper", value = True).do(move_forward)

    try:
        while True:
            time.sleep(0.5)
    except KeyboardInterrupt:
        pass

Indices and tables