Method and system for motion prior based visual odometry for ground robot navigation

A system comprising:

• a memory storing instructions;
• one or more Input/Output (I/O) interfaces;
• and
• one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to:
• obtain a plurality of inputs comprising i) a previous observation comprising an RGB image and a depth image captured at a previous time step from a robot, ii) an action prior defining an action performed by the robot at the previous time step, and iii) a current observation an RGB image and a depth image captured at a current time step obtained after performing the action by the robot;
• determine a relative pose of the robot between the previous observation and the current observation based on the plurality of inputs by using a Visual Odometry (VO) module, wherein the VO module comprises i) a Geometric Coarse Pose Estimator (GCPE) module, and ii) a Neural Fine Pose Regression (NFPR) module, wherein the GCPE module estimates a coarse relative pose of the robot using the plurality of inputs, and wherein the NFPR module determines the relative pose of the robot using the plurality of inputs and the coarse relative pose as motion prior;
• update a plurality of goal coordinates of the robot at the previous timestep based on the relative pose of the robot;
• and
• determine a next action to be performed by the robot at the current timestep based on the updated plurality of goal coordinates using a navigation policy for ground navigation by the robot.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

• obtaining a plurality of inputs comprising:
• i) a previous observation comprising an RGB image and a depth image captured at a previous time step from a robot, ii) an action prior defining an action performed by the robot at the previous time step, and iii) a current observation an RGB image and a depth image captured at a current time step obtained after performing the action by the robot;
• determining a relative pose of the robot between the previous observation and the current observation based on the plurality of inputs by using a Visual Odometry (VO) module, wherein the VO module comprises i) a Geometric Coarse Pose Estimator (GCPE) module, and ii) a Neural Fine Pose Regression (NFPR) module, wherein the GCPE module estimates a coarse relative pose of the robot using the plurality of inputs, and wherein the NFPR module determines the relative pose of the robot using the plurality of inputs and the coarse relative pose as motion prior;
• updating a plurality of goal coordinates of the robot at the previous timestep based on the relative pose of the robot;
• and
• determining a next action to be performed by the robot at the current timestep based on the updated plurality of goal coordinates using a navigation policy for ground navigation by the robot.