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use_rerun: true # Enable visualization using rerun.io
render_depth: true # Enable rendering depth
use_multithreading_depth_rendering: true # Enable multithreading for depth rendering for large resolution (above 32x24)
use_rk4_for_dynamics_update: false # Enable Runge-Kutta 4th order integration for dynamics, otherwise Euler integration is used
use_rk4_for_dynamics_control: false # Enable Runge-Kutta 4th order integration for dynamics, otherwise Euler integration is used
max_render_threads: 8 # Maximum number of threads for rendering
rerun_blueprint: "config/peng_default_blueprint.rbl"
simulation:
control_frequency: 200 # Frequency of control loop execution (Hz)
simulation_frequency: 1000 # Frequency of physics simulation updates (Hz)
log_frequency: 20 # Frequency of data logging (Hz)
duration: 90.0 # Total duration of the simulation (seconds)
quadrotor:
mass: 1.3 # Mass of the quadrotor (kg)
gravity: 9.81 # Gravitational acceleration (m/s^2)
drag_coefficient: 0.000 # Aerodynamic drag coefficient
# Inertia matrix [Ixx, Ixy, Ixz, Iyx, Iyy, Iyz, Izx, Izy, Izz] (kg*m^2)
inertia_matrix:
pid_controller:
pos_gains: # PID gains for position control
kp: # Proportional gains [x, y, z]
kd: # Derivative gains [x, y, z]
ki: # Integral gains [x, y, z]
att_gains: # PID gains for attitude control
kp: # Proportional gains [roll, pitch, yaw]
kd: # Derivative gains [roll, pitch, yaw]
ki: # Integral gains [roll, pitch, yaw]
pos_max_int: # Maximum integral error for position control [x, y, z]
att_max_int: # Maximum integral error for attitude control [roll, pitch, yaw]
imu:
accel_noise_std: 0.02 # Standard deviation of accelerometer noise (m/s^2)
gyro_noise_std: 0.01 # Standard deviation of gyroscope noise (rad/s)
accel_bias_std: 0.0001 # Standard deviation of accelerometer bias instability (m/s^2)
gyro_bias_std: 0.0001 # Standard deviation of gyroscope bias instability (rad/s)
maze:
lower_bounds: # Lower bounds of the maze [x, y, z] (m)
upper_bounds: # Upper bounds of the maze [x, y, z] (m)
num_obstacles: 20 # Number of obstacles in the maze
obstacles_velocity_bounds: # Maximum velocity of obstacles [x, y, z] (m/s)
obstacles_radius_bounds: # Range of obstacle radii [min, max] (m)
camera:
resolution: # Camera resolution [width, height] (pixels)
fov_vertical: 90 # Vertical Field of View (degrees)
near: 0.1 # Near clipping plane (m)
far: 5.0 # Far clipping plane (m)
rotation_transform: # Rotates camera to positive x-axis
mesh:
division: 7 # Number of divisions in the mesh grid
spacing: 0.5 # Spacing between mesh lines (m)
planner_schedule:
# Minimum Jerk Line trajectory
- step: 1000 # Simulation step in ms to start this planner
planner_type: MinimumJerkLine
params:
end_position: # Target end position [x, y, z] (m)
end_yaw: 0.0 # Target end yaw angle (rad)
duration: 2.5 # Duration of the trajectory (s)
# Lissajous trajectory
- step: 5000
planner_type: Lissajous
params:
center: # Center of the Lissajous curve [x, y, z] (m)
amplitude: # Amplitudes of the curve [x, y, z] (m)
frequency: # Frequencies of the curve [x, y, z] (Hz)
phase: # Phase offsets [x, y, z] (rad)
duration: 20.0 # Duration of the trajectory (s)
end_yaw: 6.283185307179586 # Target end yaw angle (2*PI rad)
ramp_time: 5.0 # Time for smooth transition (s)
# Circular trajectory
- step: 27000
planner_type: Circle
params:
center: # Center of the circle [x, y, z] (m)
radius: 0.5 # Radius of the circle (m)
angular_velocity: 1.0 # Angular velocity (rad/s)
duration: 5.0 # Duration of the trajectory (s)
ramp_time: 2.0 # Time for smooth transition (s)
# Another Minimum Jerk Line trajectory
- step: 32000
planner_type: MinimumJerkLine
params:
end_position: # Target end position [x, y, z] (m)
end_yaw: 0.0 # Target end yaw angle (rad)
duration: 3.0 # Duration of the trajectory (s)
# Obstacle Avoidance trajectory
- step: 35000
planner_type: ObstacleAvoidance
params:
target_position: # Target position [x, y, z] (m)
duration: 10.0 # Duration of the trajectory (s)
end_yaw: 0.0 # Target end yaw angle (rad)
k_att: 0.03 # Attractive force gain
k_rep: 0.01 # Repulsive force gain
k_vortex: 0.005 # Vortex force gain
d0: 0.5 # Obstacle influence distance (m)
d_target: 0.5 # Target influence distance (m)
max_speed: 0.1 # Maximum speed (m/s)
# Minimum Snap Waypoint trajectory
- step: 45000
planner_type: MinimumSnapWaypoint
params:
waypoints: # List of waypoints [x, y, z] (m)
-
-
-
-
yaws: # Yaw angles at waypoints (rad)
segment_times: # Time to reach each waypoint (s)
# Quadratic Polynomial trajectory
- step: 65000
planner_type: QPpolyTraj
params:
waypoints: # List of waypoints [x, y, z, yaw] in (m) and (rad) respectively
-
-
-
-
segment_times: # Time to reach each waypoint (s)
polynomial_order: 9 # Order of the polynomial to be used in computing trajectory
minimize_derivative: 3 # Minimize which derivative in the QP problem (1->Velocity, 2->Acceleration, 3->Snap, 4->Jerk. Please note that derivative value greater than 4 is not supported)
smooth_upto: 4 # Ensure continuity upto which derivative. NOTE: This MUST be <= polynomial_order (1->Velocity, 2->Acceleration, 3->Snap, 4->Jerk. Please note that derivative value greater than 4 is not supported)
max_velocity: 4.0 # Maximum velocity constraint. Set to 0.0 to disregard these constraints. Please set reasonable values for this as it influences solver convergence or failure.
max_acceleration: 2.0 # Maximum acceleration constraint. Set to 0.0 to disregard these constraints. Please set reasonable values for this as it influences solver convergence or failure.
dt: 0.1 # Step time used while generating inequality constraints. Has no bearing if max_velocity or max_acceleration is set to 0.0. Please set reasonable value for this as it has a huge impact on OSQP solve time.
# Landing trajectory
- step: 85000
planner_type: Landing
params:
duration: 5.0 # Duration of the landing maneuver (s)