add you own algorithm

you can add you own algorithm to Slampy by adding a new your_method_name.py file with the specs found below, to the slam_method folder

the file must contain a class named Slam with the method shown below

import sys
sys.path.append("..")
from slampy import Sensor
from slampy import State

class Slam:
    def __init__(self, params, sensor_type):

    def process_image_mono(self, image, tframe):

    def process_image_stereo(self, image_left, image_right, tframe):

    def process_image_imu_mono(self, image, tframe, imu):

    def process_image_imu_stereo(self, image_left, image_right, tframe, imu):

    def process_image_rgbd(self, image, tframe):

    def get_pose_to_target(self):

    def get_abs_cloud(self):

    def get_camera_matrix(self):

    def get_state(self):

    def reset(self):

    def shutdown(self):

Slam class references

In this section we describe all the methods with the parameters that you need to write in order to add your algorithm to Slampy.

You can add your own accessor method, but the method described below must be present with this signature and return the exact value as described

class Slam

__init__(self, params, sensor_type)

Initialize your algorithm with the params from the settings.yaml and the sensor type

Parameters

• params (dict) – the setting.yaml params conver to Python dictionary

• sensor_type (Pyslam.Sensor) – the type of the sensor as istance of Sensor Class

there are one process_image method for each of the sensor type in Sensor Class. If your algorithm hasn’t one of this methods you can add an exception every time that one calls that sensor processing method

process_image_mono(self, image, tframe)

pass the image to the slam system and compute the tracking

Parameters

• image (numpy.ndarray) – an RGB image

• tframe (float) – the timestamp in which the frame is caputred

Raises

Exception – if the Sensor is different from MONOCULAR

process_image_stereo(self, image_left, image_right, tframe)

pass the images to the slam system and compute the tracking

Parameters

• image_left (numpy.ndarray) – an RGB image

• image_right (numpy.ndarray) – an RGB image

• tframe (float) – the timestamp in which the frame is caputred

Raises

Exception – if the Sensor is different from STEREO

process_image_imu_mono(self, image, tframe, imu)

pass the image to the slam system and compute the tracking

Parameters

• image_left (numpy.ndarray) – an RGB image

• image_right (numpy.ndarray) – an RGB image

• tframe (float) – the timestamp in which the frame is caputred

• imu (numpy.ndarray) – the imu data imu data stored in an float array in the form of [ AccX ,AccY ,AccZ, GyroX, vGyroY, vGyroZ, Timestamp]

Raises

Exception – if the Sensor is different from MONOCULAR_IMU

process_image_imu_stereo(self, image_left, image_right, tframe, imu)

pass the images to the slam system and compute the tracking

Parameters

• image_left (numpy.ndarray) – an RGB image

• image_right (numpy.ndarray) – an RGB image

• tframe (float) – the timestamp in which the frame is caputred

• imu (numpy.ndarray) – the imu data imu data stored in an float array in the form of [ AccX ,AccY ,AccZ, GyroX, vGyroY, vGyroZ, Timestamp]

Raises

Exception – if the Sensor is different from STEREO_IMU

process_image_rgbd(self, image, tframe)

pass the image to the slam system and compute the tracking

Parameters

• image (numpy.ndarray) – an RGBD image

• tframe (float) – the timestamp in which the frame is caputred

Raises

Exception – if the Sensor is different from RGBD

get_pose_to_target(self)

return the pose between the references frame (usually the first frame) and the current one T.

Returns

the pose computed from the references frame to the actual ones, None if the tracking is failed

Return type

a 4x4 numpy array

get_abs_cloud(self)

return the point cloud at the current frame stored in absolute coordinates (coordinates from the references frame)

return

an array with the 3D coordinate of the point, None if the traking is failed

rtype

a nx3 numpy array

get_camera_matrix(self)

return the intrinsec parameter of cameras

return

an array with the intrinsec parameter of cameras

rtype

a 4x4 numpy array

get_state(self)

return the current state of the tracking as istance of State Class

return

the state of the tracking

rtype

Slampy.State

reset(self)

reset/initialize the slam tracking

shutdown(self)

shutdown the slam algorithm