Configure behavior for objects#

Each object in the simulation can be assigned a behavior independently to simulate different scenarios. The behavior of the object can be configured by specifying the behavior parameters in the YAML configuration file.

Behavior Configuration Parameters#

Currently, there are two built-in behaviors: dash and rvo. By default, the moving objects’ behavior is static. You can set the behavior of the object to dash or rvo in the YAML configuration file. The dash behavior is a simple behavior that moves the object from its initial position to the goal position directly. The rvo behavior is a dynamic collision avoidance algorithm for multiple agents.

The example of RVO behavior is shown below:

import irsim

env = irsim.make()   

for i in range(1000):

    env.step()
    env.render(0.05)

    if env.done():
        break

env.end()

world:
  height: 10  # the height of the world
  width: 10   # the width of the world

robot:
  - number: 10
    distribution: {name: 'circle', radius: 4.0, center: [5, 5]}  
    kinematics: {name: 'diff'}
    shape: 
      - {name: 'circle', radius: 0.2} 
    behavior: {name: 'rvo', vxmax: 1.5, vymax: 1.5, acce: 1.0, factor: 1.0}
    vel_min: [-3, -3.0]
    vel_max: [3, 3.0]
    color: ['royalblue', 'red', 'green', 'orange', 'purple', 'yellow', 'cyan', 'magenta', 'lime', 'pink', 'brown'] 
    arrive_mode: position
    goal_threshold: 0.15
    plot:
      show_trail: true
      show_goal: true
      trail_fill: true
      trail_alpha: 0.2
      show_trajectory: false
Select Parameters

Important Behavior Parameters Explained#

Common Parameters:

  • name: Behavior type ('dash', 'rvo', or custom name)

  • wander: Random goal generation after reaching current goal (default: False)

  • target_roles: Filter objects for behavior ('all', 'robot', 'obstacle')

RVO-specific Parameters:

  • vxmax/vymax: Maximum velocities in x/y directions (default: 1.5)

  • acce: Maximum acceleration (default: 1.0)

  • factor: Collision penalty weight (default: 1.0, higher = more conservative)

  • mode: Algorithm variant - 'rvo' (default), 'hrvo', or 'vo'

  • neighbor_threshold: Detection range for nearby objects (default: 3.0 meters)

Dash-specific Parameters:

  • angle_tolerance: Orientation alignment tolerance for diff/acker (default: 0.1 radians)

Full list of behavior parameters can be found in the YAML Configuration.

Advanced Configuration for Custom Behavior#

Custom Behavior Function#

If you want to create a custom behavior for the object, you should first define your own behavior in a custom python script (e.g. custom_behavior_methods.py) as shown below:

from irsim.lib import register_behavior
from irsim.util.util import relative_position, WrapToPi
import numpy as np

@register_behavior("diff", "dash_custom")
def beh_diff_dash(ego_object, objects, **kwargs):

    state = ego_object.state
    goal = ego_object.goal
    goal_threshold = ego_object.goal_threshold
    _, max_vel = ego_object.get_vel_range()
    angle_tolerance = kwargs.get("angle_tolerance", 0.1)

    behavior_vel = DiffDash2(state, goal, max_vel, goal_threshold, angle_tolerance)

    return behavior_vel


def DiffDash2(state, goal, max_vel, goal_threshold=0.1, angle_tolerance=0.2):

    distance, radian = relative_position(state, goal)

    if distance < goal_threshold:
        return np.zeros((2, 1))

    diff_radian = WrapToPi(radian - state[2, 0])
    linear = max_vel[0, 0] * np.cos(diff_radian)

    if abs(diff_radian) < angle_tolerance:
        angular = 0
    else:
        angular = max_vel[1, 0] * np.sign(diff_radian)

    return np.array([[linear], [angular]])

The ego_object is the object that you want to control, and the objects is the list of all objects in the simulation. The custom behavior function should return the velocity of the object. You can obtain the state, goal, and other properties from the objects. DiffDash2 is the custom behavior function that calculates the dash velocity of the object.

Important

You must use the @register_behavior decorator to register the custom behavior. The first argument of the decorator is the name of the kinematics (diff, acker, omni), and the second argument is the name of the behavior used in YAML file.

Register Behavior#

The python script and YAML to run the simulation with the custom behavior is shown below:

import irsim

env = irsim.make()
env.load_behavior("custom_behavior_methods")

for i in range(1000):

    env.step()
    env.render(0.01)
    
    if env.done():
        break

env.end(5)

load_behavior function loads the custom behavior methods from the python script. custom_behavior_methods is the name of the python script that contains the custom behavior function.

Note

Please place the script with the name custom_behavior_methods in the same directory as the main python script.

Now, you can use the custom behavior dash_custom in the YAML configuration file as shown below.

world:
  height: 10  # the height of the world
  width: 10   # the width of the world

robot:
  - number: 10
    distribution: {name: 'circle', radius: 4.0, center: [5, 5]}  
    kinematics: {name: 'diff'}
    shape: 
      - {name: 'circle', radius: 0.2} 
    behavior: {name: 'dash_custom'}
    vel_min: [-3, -3.0]
    vel_max: [3, 3.0]
    color: ['royalblue', 'red', 'green', 'orange', 'purple', 'yellow', 'cyan', 'magenta', 'lime', 'pink', 'brown'] 
    arrive_mode: position
    goal_threshold: 0.15
    plot:
      show_trail: true
      show_goal: true
      trail_fill: true
      trail_alpha: 0.2
      show_trajectory: false
Select Parameters