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.

from isaaclab_assets.robots.anymal import ANYMAL_C_CFG  # isort: skip


@configclass
class ImuSensorSceneCfg(InteractiveSceneCfg):
    """Design the scene with IMU 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")

    imu_LF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT")


def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
    """Run the simulator."""

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.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.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# demos should open Kit visualizer by default
 18parser.set_defaults(visualizer=["kit"])
 19# parse the arguments
 20args_cli = parser.parse_args()
 21
 22# launch omniverse app
 23app_launcher = AppLauncher(args_cli)
 24simulation_app = app_launcher.app
 25
 26"""Rest everything follows."""
 27
 28import torch
 29
 30import isaaclab.sim as sim_utils
 31from isaaclab.assets import AssetBaseCfg
 32from isaaclab.scene import InteractiveScene, InteractiveSceneCfg
 33from isaaclab.sensors import ImuCfg
 34from isaaclab.utils import configclass
 35
 36##
 37# Pre-defined configs
 38##
 39from isaaclab_assets.robots.anymal import ANYMAL_C_CFG  # isort: skip
 40
 41
 42@configclass
 43class ImuSensorSceneCfg(InteractiveSceneCfg):
 44    """Design the scene with IMU sensors on the robot."""
 45
 46    # ground plane
 47    ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
 48
 49    # lights
 50    dome_light = AssetBaseCfg(
 51        prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
 52    )
 53
 54    # robot
 55    robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
 56
 57    imu_RF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT")
 58
 59    imu_LF = ImuCfg(prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT")
 60
 61
 62def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
 63    """Run the simulator."""
 64    # Define simulation stepping
 65    sim_dt = sim.get_physics_dt()
 66    sim_time = 0.0
 67    count = 0
 68
 69    # Simulate physics
 70    while simulation_app.is_running():
 71        if count % 500 == 0:
 72            # reset counter
 73            count = 0
 74            # reset the scene entities
 75            root_pose = scene["robot"].data.default_root_pose.torch.clone()
 76            root_pose[:, :3] += scene.env_origins
 77            scene["robot"].write_root_link_pose_to_sim_index(root_pose=root_pose)
 78            root_vel = scene["robot"].data.default_root_vel.torch.clone()
 79            scene["robot"].write_root_com_velocity_to_sim_index(root_velocity=root_vel)
 80            # set joint positions with some noise
 81            joint_pos, joint_vel = (
 82                scene["robot"].data.default_joint_pos.torch.clone(),
 83                scene["robot"].data.default_joint_vel.torch.clone(),
 84            )
 85            joint_pos += torch.rand_like(joint_pos) * 0.1
 86            scene["robot"].write_joint_position_to_sim_index(position=joint_pos)
 87            scene["robot"].write_joint_velocity_to_sim_index(velocity=joint_vel)
 88            # clear internal buffers
 89            scene.reset()
 90            print("[INFO]: Resetting robot state...")
 91        # Apply default actions to the robot
 92        targets = scene["robot"].data.default_joint_pos.torch
 93        scene["robot"].set_joint_position_target_index(target=targets)
 94        scene.write_data_to_sim()
 95        # perform step
 96        sim.step()
 97        # update sim-time
 98        sim_time += sim_dt
 99        count += 1
100        # update buffers
101        scene.update(sim_dt)
102
103        # print information from the sensors
104        print("-------------------------------")
105        print(scene["imu_LF"])
106        print("Received angular velocity: ", scene["imu_LF"].data.ang_vel_b)
107        print("Received linear acceleration: ", scene["imu_LF"].data.lin_acc_b)
108        print("-------------------------------")
109        print(scene["imu_RF"])
110        print("Received angular velocity: ", scene["imu_RF"].data.ang_vel_b)
111        print("Received linear acceleration: ", scene["imu_RF"].data.lin_acc_b)
112
113
114def main():
115    """Main function."""
116
117    # Initialize the simulation context
118    sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device)
119    sim = sim_utils.SimulationContext(sim_cfg)
120    # Set main camera
121    sim.set_camera_view(eye=[3.5, 3.5, 3.5], target=[0.0, 0.0, 0.0])
122    # design scene
123    scene_cfg = ImuSensorSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0)
124    scene = InteractiveScene(scene_cfg)
125    # Play the simulator
126    sim.reset()
127    # Now we are ready!
128    print("[INFO]: Setup complete...")
129    # Run the simulator
130    run_simulator(sim, scene)
131
132
133if __name__ == "__main__":
134    # run the main function
135    main()
136    # close sim app
137    simulation_app.close()