autoware_gyro_odometer

Overview

autoware_gyro_odometer is the package to estimate twist by combining imu and vehicle speed.

Design

autoware_gyro_odometer is part of the perception or localization stack, providing reliable motion estimates for navigation and control. It is designed to estimate the robot’s motion by combining vehicle twist data (linear and angular velocities) with angular velocity measurements from an IMU (Inertial Measurement Unit).

Data Handling and Synchronization:

• Message Queues: Uses queues to store vehicle twist and gyro messages to ensure data synchronization.

• Message Timeouts: Checks for message timeouts to discard stale data, preventing incorrect estimations.

  Error Checks and Logging:

• Timeout Handling: Logs errors and clears queues if messages exceed a defined time threshold.
• Transformation Checks: Verifies that TF transforms between IMU and base frames are available; logs errors if not.

Data Processing:

• Transformation: Converts gyro data into the base frame using TF to ensure accurate angular velocity measurements.
• Mean and Covariance Calculation: Averages multiple measurements to reduce noise and calculates covariances to represent data reliability.

Output and Publishing:

• Twist Estimation: Constructs output messages with estimated twist values and covariances.
• Stationary Handling: Zeros out certain twist components when the robot is stationary to avoid noise.

Inputs / Outputs

Input

Output

Parameters

{{ json_to_markdown(“localization/autoware_gyro_odometer/schema/gyro_odometer.schema.json”) }}

Assumptions / Known limits

• [Assumption] The frame_id of input twist message must be set to base_link.

• [Assumption] The covariance in the input messages must be properly assigned.

• [Assumption] The angular velocity is set to zero if both the longitudinal vehicle velocity and the angular velocity around the yaw axis are sufficiently small. This is for suppression of the IMU angular velocity bias. Without this process, we misestimate the vehicle status when stationary.

• [Limitation] The frequency of the output messages depends on the frequency of the input IMU message.

• [Limitation] We cannot produce reliable values for the lateral and vertical velocities. Therefore we assign large values to the corresponding elements in the output covariance matrix.

Diagnostics