An Efficient Method for Accurate Pose Estimation and Error Correction of Cuboidal Objects
This addresses the need for accurate and fast pose estimation in robotics for picking tasks, but it appears incremental as it builds on existing local registration methods.
The paper tackles the problem of precise pose estimation for cuboidal objects in autonomous picking by proposing an efficient linear-time method for error correction, achieving high precision and time efficiency.
The proposed system outlined in this paper is a solution to a use case that requires the autonomous picking of cuboidal objects from an organized or unorganized pile with high precision. This paper presents an efficient method for precise pose estimation of cuboid-shaped objects, which aims to reduce errors in target pose in a time-efficient manner. Typical pose estimation methods like global point cloud registrations are prone to minor pose errors for which local registration algorithms are generally used to improve pose accuracy. However, due to the execution time overhead and uncertainty in the error of the final achieved pose, an alternate, linear time approach is proposed for pose error estimation and correction. This paper presents an overview of the solution followed by a detailed description of individual modules of the proposed algorithm.