_scenario.addBody(createSingleBody('sphere_' + str(i), 'sphere'))
for i in range(NUM_CYLINDERS):
_scenario.addBody(createSingleBody('cylinder_' + str(i), 'cylinder'))
for i in range(NUM_CAPSULES):
_scenario.addBody(createSingleBody('capsule_' + str(i), 'capsule'))
for i in range(NUM_MESHES):
_scenario.addBody(createSingleBody('mesh_' + str(i), 'mesh'))
_agent = tysoc_bindings.PyCoreAgent('agent0', [-1, 0, 3], 'urdf', 'dogbot')
_scenario.addAgent(_agent)
_runtime = pytysoc.createRuntime(
physicsBackend=pytysoc.BACKENDS.PHYSICS.MUJOCO,
renderingBackend=pytysoc.BACKENDS.RENDERING.GLVIZ)
_simulation = _runtime.createSimulation(_scenario)
_visualizer = _runtime.createVisualizer(_scenario)
_simulation.initialize()
_visualizer.initialize()
_simulation.step()
_visualizer.render()
_running = False
while _visualizer.isActive():
"""
Basic task sample: Here we create a task which contains a group of ...
agent(s), terrain generator(s) and sensor(s).
"""
import time
import numpy as np
import pytysoc
_runtime = pytysoc.createRuntime(physicsBackend='mujoco',
renderingBackend='custom',
renderingMode='interactive',
renderingConfigParams={})
_task = _runtime.createTask(
taskType=pytysoc.tasks.SINGLE_WALK_FORWARD,
agentType=pytysoc.agents.HUMANOID,
terrainType=pytysoc.terrain.SIMPLE_PROCEDURAL_FORWARD,
terrainConfigParams={'sectionDepth': 1.0},
agentSensors=[
pytysoc.sensors.INTRINSIC, pytysoc.sensors.TERRAIN_PROFILE,
pytysoc.sensors.FRONT_CAMERA
])
## _task = _runtime.createTask( taskType = pytysoc.tasks.SINGLE_WALK_FORWARD,
## agentType = pytysoc.agents.HUMANOID,
## terrainType = pytysoc.terrain.SIMPLE_PROCEDURAL_FORWARD,
## terrainConfigFile = 'procedural_forward.json',
## agentSensors = [ pytysoc.sensors.INTRINSIC,
## pytysoc.sensors.TERRAIN_PROFILE,