SLAM

The SLAM component is part of the sensor dynamics component. It provides additional accuracy for the pose estimate of the stereo INS. When the rc_visard moves through the world, the pose estimate slowly accumulates errors over time. The SLAM component can correct these pose errors by recognizing previously visited places.

The acronym SLAM stands for Simultaneous Localization and Mapping. The SLAM component creates a map consisting of the image features as used in the visual odometry component. The map is later used to correct accumulated pose errors. This is most apparent in applications where, e.g., a robot returns to a previously visited place after covering a large distance (this is called a loop closure). In this case, the robot can re-detect image features that are already stored in its map and can use this information to correct the drift in the pose estimate that accumulated since the last visit.

When closing a loop, not only the current pose, but also the past pose estimates (the trajectory of the rc_visard), are corrected. Continuous trajectory correction leads to a more accurate map. On the other hand, the accuracy of the full trajectory is important when it is used to build an integrated world model, e.g., by projecting the 3D point clouds obtained (see Computing depth images and point clouds) into a common coordinate frame. The full trajectory can be requested from the SLAM component for this purpose.

Note

The SLAM component is optionally available for the rc_visard and will run on board the sensor. If a SLAM license is stored on the rc_visard, then the SLAM component is shown as Available on the Web GUI’s Overview page and in the License section of the System page.

Usage

The SLAM component can be activated at any time, either via the rc_dynamics interface (see the documentation of the respective Services) or from the Dynamics page of the Web GUI.

The pose estimate of the SLAM component will be initialized with the current estimate of the stereo INS - and thus the origin will be where the stereo INS was started.

Since the SLAM component builds on the motion estimates of the stereo INS component, the latter will automatically be started up if it is not yet running when SLAM is started.

When the SLAM component is running, the corrected pose estimates will be available via the datastreams pose, pose_rt, and dynamics of the rc_dynamics component.

The full trajectory is available through the service get_trajectory, see Services below for details.

Memory limitations

In contrast to the other software components running on the rc_visard, the SLAM component needs to accumulate data over time, e.g., motion measurements and image features. Further, the optimization of the trajectory requires substantial amounts of memory, particularly when closing large loops. Therefore the memory requirements of the SLAM component increase over time.

Given the memory limitations of the hardware, the SLAM component needs to reduce its own memory footprint when running continuously. When the available memory runs low, the SLAM component will fix parts of the trajectory, i.e. no further optimization will be done on these parts. A minimum of 10 minutes of the trajectory will be kept unfixed at all times.

When the available memory runs low despite the above measures, two options are available. The first option is that the SLAM component automatically goes to the HALTED state, where it stops processing, but the trajectory (up to the stopping time) is still available. This is the default behavior.

The second option is to keep running until the memory is exhausted. In that case, the SLAM component will be restarted. If the autorecovery parameter is set to true, the SLAM component will recover its previous position and resume mapping. Otherwise it will go to FATAL state, requiring to be restarted via the rc_dynamics interface (see Services).

The operation time until the memory limit is reached is strongly dependent on the trajectory of the sensor.

Parameters

The SLAM component is called rc_slam in the REST-API. The user can change the SLAM parameters using the REST-API interface.

Parameter overview

This component offers the following run-time parameters.

Table 20 The rc_slam component’s run-time parameters
Name Type Min Max Default Description
autorecovery bool False True True In case of fatal errors recover corrected position and restart mapping
halt_on_low_memory bool False True True When the memory runs low, go to halted state

This component reports the following status values.

Table 21 The rc_slam component’s status values
Name Description
state The current state of the rc_slam node
trajectory_poses Number of poses in the estimated trajectory

The reported state can take one of the following values.

Table 22 Possible states of the rc_slam component
State name Description
IDLE The component is ready, but idle. No trajectory data is available.
WAITING_FOR_DATA The component was started but is waiting for data from stereo INS or VO.
RUNNING The component is running.
HALTED The component is stopped. The trajectory data is still available. No new information is processed.
RESETTING The component is being stopped and the internal data is being cleared.
RESTARTING The component is being restarted.
FATAL A fatal error has occured.

Services

The SLAM component offers the following services.

Note

Activation and deactivation of the SLAM component is done via the service interface of rc_dynamics (see Services).

reset

clears the internal state of the SLAM component. This service is to be used after stopping the SLAM component using the rc_dynamics interface (see the respective Services). The SLAM component maintains the estimate of the full trajectory even when stopped. This service clears this estimate and frees the respective memory. The returned status is RESETTING.

This service requires no arguments.

This service returns the following response:

{
  "accepted": "bool",
  "current_state": "string"
}
get_trajectory
With this service call the trajectory can be retrieved. The service arguments allow to select a subsection of the trajectory by defining a start_time and an end_time. Both are optional, i.e., they could be left empty or filled with zero values, which results in the subsection to include the trajectory from the very beginning, or to the very end, respectively, or both. If not empty or zero, they can be defined either as absolute timestamps or to be relative to the trajectory (start_time_relative and end_time_relative flags). If defined to be relative, the values’ signs indicate to which point in time they relate to: Positive values define an offset to the trajectory start time; negative values are interpreted as an offset from the trajectory end time. The below diagram illustrates three examples for the relative parameterization.
_images/rc_slam_get_trajectory_examples_en.png

Fig. 41 Examples for combinations of relative start and end times for the get_trajectory service. All combinations shown select the same subset of the trajectory.

Note

A relative start_time of zero will select everything from the start of the trajectory, whereas a relative end_time of zero will select everything to the end of the trajectory.

This service requires the following arguments:

{
  "end_time": {
    "nsec": "int32",
    "sec": "int32"
  },
  "end_time_relative": "bool",
  "start_time": {
    "nsec": "int32",
    "sec": "int32"
  },
  "start_time_relative": "bool"
}

This service returns the following response:

{
  "trajectory": {
    "name": "string",
    "parent": "string",
    "poses": [
      {
        "pose": {
          "orientation": {
            "w": "float64",
            "x": "float64",
            "y": "float64",
            "z": "float64"
          },
          "position": {
            "x": "float64",
            "y": "float64",
            "z": "float64"
          }
        },
        "timestamp": {
          "nsec": "int32",
          "sec": "int32"
        }
      }
    ],
    "producer": "string",
    "timestamp": {
      "nsec": "int32",
      "sec": "int32"
    }
  }
}