Inertial Measurement Unit (IMU)

Inertial Measurement Unit (IMU)#

A diagram outlining the basic force relationships for the IMU sensor

Inertial Measurement Units (IMUs) are a type of sensor for measuring the acceleration of an object. These sensors are traditionally designed report linear accelerations and angular velocities, and function on similar principles to that of a digital scale: They report accelerations derived from net force acting on the sensor.

A naive implementation of an IMU would report a negative acceleration due to gravity while the sensor is at rest in some local gravitational field. This is not generally needed for most practical applications, and so most real IMU sensors often include a gravity bias and assume that the device is operating on the surface of the Earth. The IMU we provide in Isaac Lab includes a similar bias term, which defaults to +g. This means that if you add an IMU to your simulation, and do not change this bias term, you will detect an acceleration of \(+ 9.81 m/s^{2}\) anti-parallel to gravity acceleration.

Consider a simple environment with an Anymal Quadruped equipped with an IMU on each of its two front feet.


@configclass
class ImuSensorSceneCfg(InteractiveSceneCfg):
    """Design the scene with sensors on the robot."""

    # ground plane
    ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())

    # lights
    dome_light = AssetBaseCfg(
        prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
    )

    # robot
    robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")

    imu_RF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT", debug_vis=True)

    imu_LF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT", gravity_bias=(0, 0, 0), debug_vis=True)


def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
    """Run the simulator."""
    # Define simulation stepping
    sim_dt = sim.get_physics_dt()

Here we have explicitly removed the bias from one of the sensors, and we can see how this affects the reported values by visualizing the sensor when we run the sample script

IMU visualized

Notice that the right front foot explicitly has a bias of (0,0,0). In the visualization, you should see that the arrow indicating the acceleration from the right IMU rapidly changes over time, while the arrow visualizing the left IMU points constantly along the vertical axis.

Retrieving values form the sensor is done in the usual way

def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
  .
  .
  .
  # Simulate physics
  while simulation_app.is_running():
    .
    .
    .
    # print information from the sensors
    print("-------------------------------")
    print(scene["imu_LF"])
    print("Received linear velocity: ", scene["imu_LF"].data.lin_vel_b)
    print("Received angular velocity: ", scene["imu_LF"].data.ang_vel_b)
    print("Received linear acceleration: ", scene["imu_LF"].data.lin_acc_b)
    print("Received angular acceleration: ", scene["imu_LF"].data.ang_acc_b)
    print("-------------------------------")
    print(scene["imu_RF"])
    print("Received linear velocity: ", scene["imu_RF"].data.lin_vel_b)
    print("Received angular velocity: ", scene["imu_RF"].data.ang_vel_b)
    print("Received linear acceleration: ", scene["imu_RF"].data.lin_acc_b)
    print("Received angular acceleration: ", scene["imu_RF"].data.ang_acc_b)

The oscillations in the values reported by the sensor are a direct result of of how the sensor calculates the acceleration, which is through a finite difference approximation between adjacent ground truth velocity values as reported by the sim. We can see this in the reported result (pay attention to the linear acceleration) because the acceleration from the right foot is small, but explicitly zero.

Imu sensor @ '/World/envs/env_.*/Robot/LF_FOOT':
        view type         : <class 'omni.physics.tensors.impl.api.RigidBodyView'>
        update period (s) : 0.0
        number of sensors : 1

Received linear velocity:  tensor([[ 0.0203, -0.0054,  0.0380]], device='cuda:0')
Received angular velocity:  tensor([[-0.0104, -0.1189,  0.0080]], device='cuda:0')
Received linear acceleration:  tensor([[ 4.8344, -0.0205,  8.5305]], device='cuda:0')
Received angular acceleration:  tensor([[-0.0389, -0.0262, -0.0045]], device='cuda:0')
-------------------------------
Imu sensor @ '/World/envs/env_.*/Robot/RF_FOOT':
        view type         : <class 'omni.physics.tensors.impl.api.RigidBodyView'>
        update period (s) : 0.0
        number of sensors : 1

Received linear velocity:  tensor([[0.0244, 0.0077, 0.0431]], device='cuda:0')
Received angular velocity:  tensor([[ 0.0122, -0.1360, -0.0042]], device='cuda:0')
Received linear acceleration:  tensor([[-0.0018,  0.0010, -0.0032]], device='cuda:0')
Received angular acceleration:  tensor([[-0.0373, -0.0050, -0.0053]], device='cuda:0')
-------------------------------
Code for imu_sensor.py
  1# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
  2# All rights reserved.
  3#
  4# SPDX-License-Identifier: BSD-3-Clause
  5
  6"""Launch Isaac Sim Simulator first."""
  7
  8import argparse
  9
 10from isaaclab.app import AppLauncher
 11
 12# add argparse arguments
 13parser = argparse.ArgumentParser(description="Example on using the IMU sensor.")
 14parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to spawn.")
 15# append AppLauncher cli args
 16AppLauncher.add_app_launcher_args(parser)
 17# parse the arguments
 18args_cli = parser.parse_args()
 19
 20# launch omniverse app
 21app_launcher = AppLauncher(args_cli)
 22simulation_app = app_launcher.app
 23
 24"""Rest everything follows."""
 25
 26import torch
 27
 28import isaaclab.sim as sim_utils
 29from isaaclab.assets import AssetBaseCfg
 30from isaaclab.scene import InteractiveScene, InteractiveSceneCfg
 31from isaaclab.sensors import ImuCfg
 32from isaaclab.utils import configclass
 33
 34##
 35# Pre-defined configs
 36##
 37from isaaclab_assets.robots.anymal import ANYMAL_C_CFG  # isort: skip
 38
 39
 40@configclass
 41class ImuSensorSceneCfg(InteractiveSceneCfg):
 42    """Design the scene with sensors on the robot."""
 43
 44    # ground plane
 45    ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
 46
 47    # lights
 48    dome_light = AssetBaseCfg(
 49        prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
 50    )
 51
 52    # robot
 53    robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
 54
 55    imu_RF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT", debug_vis=True)
 56
 57    imu_LF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT", gravity_bias=(0, 0, 0), debug_vis=True)
 58
 59
 60def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
 61    """Run the simulator."""
 62    # Define simulation stepping
 63    sim_dt = sim.get_physics_dt()
 64    sim_time = 0.0
 65    count = 0
 66
 67    # Simulate physics
 68    while simulation_app.is_running():
 69        if count % 500 == 0:
 70            # reset counter
 71            count = 0
 72            # reset the scene entities
 73            # root state
 74            # we offset the root state by the origin since the states are written in simulation world frame
 75            # if this is not done, then the robots will be spawned at the (0, 0, 0) of the simulation world
 76            root_state = scene["robot"].data.default_root_state.clone()
 77            root_state[:, :3] += scene.env_origins
 78            scene["robot"].write_root_link_pose_to_sim(root_state[:, :7])
 79            scene["robot"].write_root_com_velocity_to_sim(root_state[:, 7:])
 80            # set joint positions with some noise
 81            joint_pos, joint_vel = (
 82                scene["robot"].data.default_joint_pos.clone(),
 83                scene["robot"].data.default_joint_vel.clone(),
 84            )
 85            joint_pos += torch.rand_like(joint_pos) * 0.1
 86            scene["robot"].write_joint_state_to_sim(joint_pos, joint_vel)
 87            # clear internal buffers
 88            scene.reset()
 89            print("[INFO]: Resetting robot state...")
 90        # Apply default actions to the robot
 91        # -- generate actions/commands
 92        targets = scene["robot"].data.default_joint_pos
 93        # -- apply action to the robot
 94        scene["robot"].set_joint_position_target(targets)
 95        # -- write data to sim
 96        scene.write_data_to_sim()
 97        # perform step
 98        sim.step()
 99        # update sim-time
100        sim_time += sim_dt
101        count += 1
102        # update buffers
103        scene.update(sim_dt)
104
105        # print information from the sensors
106        print("-------------------------------")
107        print(scene["imu_LF"])
108        print("Received linear velocity: ", scene["imu_LF"].data.lin_vel_b)
109        print("Received angular velocity: ", scene["imu_LF"].data.ang_vel_b)
110        print("Received linear acceleration: ", scene["imu_LF"].data.lin_acc_b)
111        print("Received angular acceleration: ", scene["imu_LF"].data.ang_acc_b)
112        print("-------------------------------")
113        print(scene["imu_RF"])
114        print("Received linear velocity: ", scene["imu_RF"].data.lin_vel_b)
115        print("Received angular velocity: ", scene["imu_RF"].data.ang_vel_b)
116        print("Received linear acceleration: ", scene["imu_RF"].data.lin_acc_b)
117        print("Received angular acceleration: ", scene["imu_RF"].data.ang_acc_b)
118
119
120def main():
121    """Main function."""
122
123    # Initialize the simulation context
124    sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device)
125    sim = sim_utils.SimulationContext(sim_cfg)
126    # Set main camera
127    sim.set_camera_view(eye=[3.5, 3.5, 3.5], target=[0.0, 0.0, 0.0])
128    # design scene
129    scene_cfg = ImuSensorSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0)
130    scene = InteractiveScene(scene_cfg)
131    # Play the simulator
132    sim.reset()
133    # Now we are ready!
134    print("[INFO]: Setup complete...")
135    # Run the simulator
136    run_simulator(sim, scene)
137
138
139if __name__ == "__main__":
140    # run the main function
141    main()
142    # close sim app
143    simulation_app.close()