| Version 6 (modified by , 10 years ago) ( diff ) |
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Table of Contents
Tutorial
This is a draft version.
Vocabulary
Before we dive into this tutorial, lets define a few words. I tried to use commonly used vocabulary, and hope I did understand them correclty. Feel free to contact me if you find mistakes.
- IK: Inverse Kinematic
Simple example
Py4bot is just a framework, so it is up to you to write the application matching your robot. But don't worry, it is very easy.
As Py4bot has a nice 3D simulation engine, based on ​VPython, for this example, we are going to setup an application for a simulated 3DoF hexapod.
All usefull classes are available from the api.py module. So, we just have to import things from here. Let's create a hexapod.py file to put our code, and import what we are going to use in this tutorial:
# -*- coding: utf-8 -*- from py4bot import api as api4bot
Now, let's create the robot! A multi-legs robot is mainly build from a body, and several legs. In most cases, the defaut body provided by Py4bot is OK, but in any case, we need to create legs.
The second thing we also need to create is the actuator pool, which contain all legs joints. In our example, joints are standard servos. So, here is what the main robot class looks like:
import settings class Hexapod(api4bot.Robot): def _createLegs(self): legs = {} legIk = {} for legIndex in settings.LEGS_INDEX: legs[legIndex] = api4bot.Leg3Dof(legIndex, {'coxa': Coxa(), 'femur': Femur(), 'tibia': Tibia()}) legIk[legIndex] = api4bot.Leg3DofIk(settings.LEGS_GEOMETRY[legIndex]) return legs, legIk def _createActuatorPool(self): driver = api4bot.VPython3Dof(settings.LEGS_INDEX, settings.LEGS_GEOMETRY, settings.LEGS_ORIGIN, settings.LEGS_SERVOS_MAPPING) pool = api4bot.ActuatorPool(driver) for leg in self._legs.values(): # Create joints actuators num = settings.LEGS_SERVOS_MAPPING[leg.index]['coxa'] actuator = pool.create(leg.coxa, num) pool.add(actuator) num = settings.LEGS_SERVOS_MAPPING[leg.index]['femur'] actuator = pool.create(leg.femur, num) pool.add(actuator) num = settings.LEGS_SERVOS_MAPPING[leg.index]['tibia'] actuator = pool.create(leg.tibia, num) pool.add(actuator) return pool
As you can see, we just implemented 2 virtual methods, _createLegs() and _createActuatorPool().
Also note that we used some values from the settings.py module. This module is just a simple way to centralise the configuration of our hexapod.
For now, it should contain something like:
# -*- coding: utf-8 -*- from py4bot import api as api4bot # Legs index LEGS_INDEX = ('RF', 'RM', 'RR', 'LR', 'LM', 'LF') # Legs geometry LEGS_GEOMETRY = { 'RM': {'coxa': 25, 'femur': 45, 'tibia': 50}, 'RF': {'coxa': 25, 'femur': 45, 'tibia': 50}, 'LF': {'coxa': 25, 'femur': 45, 'tibia': 50}, 'LM': {'coxa': 25, 'femur': 45, 'tibia': 50}, 'LR': {'coxa': 25, 'femur': 45, 'tibia': 50}, 'RR': {'coxa': 25, 'femur': 45, 'tibia': 50} } # Legs origin LEGS_ORIGIN = { 'RM': {'x': 50., 'y': 0., 'gamma0' : 0.}, 'RF': {'x': 35., 'y': 80., 'gamma0' : 30.}, 'LF': {'x': -35., 'y': 80., 'gamma0' : 150.}, 'LM': {'x': -50., 'y': 0., 'gamma0' : 180.}, 'LR': {'x': -35., 'y': -80., 'gamma0' : 210.}, 'RR': {'x': 35., 'y': -80., 'gamma0' : 330.}, } api4bot.config.initOrigin(LEGS_INDEX, LEGS_ORIGIN) # Legs (feet) neutral position (femur horizontal, tibia vertical) LEGS_NEUTRAL = { 'RM': { 'l': LEGS_GEOMETRY['RM']['coxa'] + LEGS_GEOMETRY['RM']['femur'], 'z': LEGS_GEOMETRY['RM']['tibia'] }, 'RF': { 'l': LEGS_GEOMETRY['RF']['coxa'] + LEGS_GEOMETRY['RF']['femur'], 'z': LEGS_GEOMETRY['RF']['tibia'] }, 'LF': { 'l': LEGS_GEOMETRY['LF']['coxa'] + LEGS_GEOMETRY['LF']['femur'], 'z': LEGS_GEOMETRY['LF']['tibia'] }, 'LM': { 'l': LEGS_GEOMETRY['LM']['coxa'] + LEGS_GEOMETRY['LM']['femur'], 'z': LEGS_GEOMETRY['LM']['tibia'] }, 'LR': { 'l': LEGS_GEOMETRY['LR']['coxa'] + LEGS_GEOMETRY['LR']['femur'], 'z': LEGS_GEOMETRY['LR']['tibia'] }, 'RR': { 'l': LEGS_GEOMETRY['RR']['coxa'] + LEGS_GEOMETRY['RR']['femur'], 'z': LEGS_GEOMETRY['RR']['tibia'] } } api4bot.config.initNeutral(LEGS_INDEX, LEGS_NEUTRAL) # Legs / servos mapping LEGS_SERVOS_MAPPING = { 'RF': {'coxa': 0, 'femur': 1, 'tibia': 2}, 'RM': {'coxa': 4, 'femur': 5, 'tibia': 6}, 'RR': {'coxa': 8, 'femur': 9, 'tibia': 10}, 'LR': {'coxa': 15, 'femur': 14, 'tibia': 13}, 'LM': {'coxa': 19, 'femur': 18, 'tibia': 17}, 'LF': {'coxa': 23, 'femur': 22, 'tibia': 21} }
Some of these values seem obvious, some don't; we'll discuss all this later.
We need to create our remote control, in order to drive our simulated robot. for this example, let's use an old gamepad, a ​Thrustmaster Firestorm Dual Analog 3. As I own such gamepad, I already added support in Py4bot.
Back in hexapod.py:
class Gamepad(api4bot.RemoteControl): def _createFrontend(self): return FrontendFactory().create("thrustmaster", path=THRUSTMASTER_PATH) def _buildComponents(self): self._addButton(command=api4bot.GaitSequencer().walkStop, key="button_000") self._addButton(command=api4bot.GaitSequencer().walkStep, key="button_003") self._addButton(command=api4bot.GaitSequencer().selectPrevGait, key="button_009", trigger="hold") self._addButton(command=api4bot.GaitSequencer().selectNextGait, key="button_008", trigger="hold") self._addJoystick(command=api4bot.GaitSequencer().walk, keys=("analog_02", "analog_03", "analog_00"), mapper=api4bot.MapperWalk()) self._addButton(command=self.robot.incBodyPosition, key="button_004", mapper=api4bot.MapperSetValue(dz=+5)) self._addButton(command=self.robot.incBodyPosition, key="button_005", mapper=api4bot.MapperSetValue(dz=-5)) self._addAnalog(command=self.robot.setBodyExtraPosition, key="analog_01", modifier="button_006", mapper=api4bot.MapperSet('z'))
Now, let's create our robot. Still in hexapod.py, add:
def main(): robot = Hexapod()
The main interrest of a multi-legs robot is to make it walk! But by default, the Robot class does not know any gait, so, we have to teach it how to actually walk.
Again, as Py4bot is a framework, it comes with some pre-defined gaits. So, all we have to do is to tell our robot which gaits to use (at least one), and give some params:
for gaitName in settings.GAITS:
legsIndexGroups = settings.GAIT_LEGS_GROUPS[gaitName]
gaitParams = settings.GAIT_PARAMS[gaitName]
gait = api4bot.GaitFactory().create(gaitName, legsIndexGroups, gaitParams)
api4bot.GaitManager().add(gait)
Let's see what wee need to add in the settings.py module:
# Gaits definitions GAITS = ("tripod", "tetrapod", "riple", "metachronal", "wave") GAIT_LEGS_GROUPS = { 'tripod': (('RM', 'LF', 'LR'), ('RF', 'LM', 'RR')), 'tetrapod': (('RR', 'LM'), ('RF', 'LR'), ('RM', 'LF')), 'riple': (('RR',), ('LM',), ('RF',), ('LR',), ('RM',), ('LF',)), 'metachronal': (('RR',), ('LM',), ('RF',), ('LR',), ('RM',), ('LF',)), 'wave': (('RR',), ('RM',), ('RF',), ('LR',), ('LM',), ('LF',)) } GAIT_PARAMS = { 'tripod': {'length': 40., 'angle': 10., 'height': 40., 'minLength': 4., 'minAngle': 2., 'speedMin': 50., 'speedMax': 200.}, 'tetrapod': {'length': 40., 'angle': 10., 'height': 30., 'minLength': 4., 'minAngle': 2., 'speedMin': 50., 'speedMax': 200.}, 'riple': {'length': 40., 'angle': 10., 'height': 30., 'minLength': 4., 'minAngle': 2., 'speedMin': 50., 'speedMax': 300.}, 'metachronal': {'length': 40., 'angle': 10., 'height': 30., 'minLength': 4., 'minAngle': 2., 'speedMin': 50., 'speedMax': 200.}, 'wave': {'length': 40., 'angle': 10., 'height': 30., 'minLength': 4., 'minAngle': 2., 'speedMin': 50., 'speedMax': 200.} }
Final steps are: instanciate the gamepad, launch the gait sequencer, and run the robot!
remote = Gamepad(robot)
GaitSequencer().start()
remote.start()
robot.setBodyPosition(z=-100)
GaitManager().select("riple")
robot.mainLoop()
remote.stop()
remote.join()
GaitSequencer().stop()
GaitSequencer().join()
More complexe example
Have a look at py4bot/examples/cronos, which contain the code for my 4DoF hexapod
Conclusion
That's it for now with this tutorial. This is the first working dev. release; their are many additional things to do, and final implementation may change, according to feedback/suggestions I will get. But the core is there. Again, the goal of this framework is to provide a high level tool to build complete and powerfull applications to control you multi-legs robots.
