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Configure interactive, path-following, and data-based driver systems for wheeled and tracked vehicles.
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Basado en la clasificación ocupacional SOC
Entry point for FSI-coupled hybrid plans (plan_type=fsi_in_scene) — any scene combining SPH fluid (water tanks, dam-break, wave channels) with multi-body dynamics, optionally with a wheeled vehicle. Pick this over mbs_in_scene whenever the plan involves a fluid domain (scene_objects with domain_type starting "sph_") or an FSI body registration (scene_objects with fsi_registration set). Routes to fsi/sph (always), veh/wheeled_vehicle (when vehicle present), and enforces FSI-specific invariants distinct from generic mbs_in_scene rigid scenes.
Entry point for rigid-body hybrid plans (plan_type=mbs_in_scene) combining a robot or vehicle with scene assets — NO fluid coupling. Routes to the correct domain skills and defines only high-level invariants. Use core/fsi_in_scene instead when the plan involves SPH fluid or FSI body registration.
Entry point for pure multi-body simulation plans (plan_type=mbs). Routes the agent to the correct mechanics, system, and camera skills and defines only high-level invariants.
Entry point for static scene plans (plan_type=scene). Routes the agent to the correct scene, system, and camera skills and defines only high-level invariants.
Set up SPH-based Fluid-Structure Interaction (FSI): create ChFsiFluidSystemSPH and ChFsiSystemSPH, configure fluid and SPH parameters, seed fluid particles with hydrostatic initialization, add container BCE boundary markers, register floating rigid bodies, optionally couple with a wheeled vehicle, and advance with sysFSI.DoStepDynamics(dT).
Translate a `geometry_relations` entry from the plan into correct PyChrono coordinate code. Read this whenever the plan declares a relation_name you have not previously encoded, and especially BEFORE writing SetPos / camera placement for any body that participates in a multi-body geometric constraint. Each subsection below is one canonical pattern named exactly as it appears in `plan.geometry_relations[i].relation_name`.
| name | driver |
| description | Configure interactive, path-following, and data-based driver systems for wheeled and tracked vehicles. |
| compatibility | pychrono >= 8.0 |
| metadata | {"domain":"veh"} |
Configure driver systems to control wheeled or tracked vehicles — interactive (keyboard), path-following (autonomous), or pre-recorded data. Driver systems work the same for both vehicle types via veh_obj.GetVehicle().
When the user asks to drive a vehicle, follow a path, or record vehicle inputs.
This codegen pipeline runs simulations headless (Xvfb / no
keyboard / no GUI input loop). ChInteractiveDriver is a
keyboard-input driver — its GetInputs() returns whatever the user
last typed at the SDL window, and in a headless run that's always
zero. The vehicle never accelerates, never steers, and the run
looks identical to a "missing physics" bug.
Pick one of the autonomous drivers below for every generated simulation:
| Need | Use |
|---|---|
| Open-loop schedule (fixed throttle/brake/steering at known times) | veh.ChDataDriver with veh.DataDriverEntry(t, s, th, br, g) entries |
| Closed-loop on vehicle state (e.g. throttle depends on x-position, brake when speed > X) | Plain veh.DriverInputs() struct, write fields each step |
| Path following with target speed | veh.ChPathFollowerDriver |
Do NOT instantiate ChInteractiveDriver in generated code. The
Interactive Driver section below is documented for reference only —
it is the wrong tool for this pipeline.
For human-in-the-loop or scripted driving:
driver = veh.ChInteractiveDriver(veh_obj.GetVehicle())
# Time to reach max steering/throttle/braking
steering_time = 1.0 # seconds to go 0 -> +1 steering
throttle_time = 1.0 # seconds to go 0 -> +1 throttle
braking_time = 0.3 # seconds to go 0 -> +1 brake
driver.SetSteeringDelta(render_step_size / steering_time)
driver.SetThrottleDelta(render_step_size / throttle_time)
driver.SetBrakingDelta(render_step_size / braking_time)
driver.Initialize()
# In simulation loop
driver_inputs = driver.GetInputs()
driver.Synchronize(time)
driver.Advance(step_size)
For autonomous path following with cruise control:
# Create path (ISO double lane change to left)
path = veh.DoubleLaneChangePath(
start, # initial position ChVector3d
13.5, # length
4.0, # width
11.0, # offset
50.0, # total length
True # to left
)
# Create path-following driver
target_speed = 12 # m/s
driver = veh.ChPathFollowerDriver(
veh_obj.GetVehicle(),
path,
"my_path",
target_speed
)
# Configure controllers
driver.GetSteeringController().SetLookAheadDistance(5.0)
driver.GetSteeringController().SetGains(0.8, 0, 0) # KP, KI, KD
driver.GetSpeedController().SetGains(0.4, 0, 0)
driver.Initialize()
# In simulation loop
driver_inputs = driver.GetInputs()
driver.Synchronize(time)
driver.Advance(step_size)
veh.DoubleLaneChangePath(start, length, width, offset, total_length, to_left)
# Creates an ISO double lane change maneuver path
For pre-recorded input sequences:
# Create data entries: (time, steering, throttle, braking, gear)
driver_data = veh.vector_Entry([
veh.DataDriverEntry(0.0, 0.0, 0.0, 0.0, 0.0),
veh.DataDriverEntry(0.5, 0.0, 0.0, 0.0, 0.0),
veh.DataDriverEntry(0.7, 0.3, 0.7, 0.0, 0.0),
veh.DataDriverEntry(1.0, 0.3, 0.7, 0.0, 0.0),
veh.DataDriverEntry(3.0, 0.5, 0.1, 0.0, 0.0)
])
driver = veh.ChDataDriver(veh_obj.GetVehicle(), driver_data)
driver.Initialize()
# In simulation loop
driver_inputs = driver.GetInputs()
driver.Synchronize(time)
driver.Advance(step_size)
The driver_inputs object has these fields:
driver_inputs.m_steering # -1 to +1
driver_inputs.m_throttle # 0 to +1
driver_inputs.m_braking # 0 to +1
driver_inputs.m_gear # gear index
In the simulation loop, synchronize in this order:
driver.Synchronize(time)
terrain.Synchronize(time)
veh_obj.Synchronize(time, driver_inputs, terrain)
vis.Synchronize(time, driver_inputs)
# Get sentinel and target locations for visualization
pS = driver.GetSteeringController().GetSentinelLocation()
pT = driver.GetSteeringController().GetTargetLocation()
# Visualize with sphere markers
ballS = vis.GetSceneManager().addSphereSceneNode(0.1)
ballT = vis.GetSceneManager().addSphereSceneNode(0.1)
ballS.setPosition(irr.vector3df(pS.x, pS.y, pS.z))
ballT.setPosition(irr.vector3df(pT.x, pT.y, pT.z))
vis.SetChaseCamera(trackPoint, distance, offset)
# trackPoint: ChVector3d — point on chassis to follow
# distance: float — camera distance behind vehicle
# offset: float — camera height offset
When visualizing with veh.ChWheeledVehicleVisualSystemVSG, attach the driver to the vis system so the HUD bars (steering / throttle / brake) render and reflect the live inputs:
vis.AttachVehicle(veh_obj.GetVehicle())
vis.AttachDriver(driver) # enables input-bar HUD
vis.Initialize()
# In the simulation loop, pass the same inputs through:
driver_inputs = driver.GetInputs()
driver.Synchronize(time)
vis.Synchronize(time, driver_inputs) # HUD picks up from here
AttachDriver only affects visualization — the driver still drives the vehicle via the vehicle.Synchronize(time, driver_inputs, terrain) path regardless.
For vehicle setup and system creation:
../../mbs/system_create/ — ChSystem creation../wheeled_vehicle/ — Vehicle creation + ChWheeledVehicleVisualSystemVSG pattern (also carries the authoritative Synchronize/Advance order for SCM-backed setups)../terrain/ — Terrain creation (Rigid / SCM / CRM)allowed_classes:
allowed_methods:
allowed_constants:
allowed_utils: