Lakshadeep Naik

Lakshadeep Naik

PhD candidate at University of Southern Denmark (SDU)

Multi-view object pose distribution tracking for pre-grasp planning on mobile robots

URL: https://doi.org/10.1109/ICRA46639.2022.9812339

Abstract: The ability to track the 6D pose distribution of an object when a mobile manipulator robot is still approaching the object can enable the robot to pre-plan grasps that combine base and arm motion. However, tracking a 6D object pose distribution from a distance can be challenging due to the limited view of the robot camera. In this work, we present a framework that fuses observations from external stationary cameras with a moving robot camera and sequentially tracks it in time to enable 6D object pose distribution tracking from a distance. We model the object pose posterior as a multi-modal distribution which results in a better performance against uncertainties introduced by large camera-object distance, occlusions and object geometry.

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Dataset used for evaluation

Recommended citation: Naik, L., Iversen, T. M., Kramberger, A., Wilm, J., & Krüger, N. (Accepted/In press). Multi-view object pose distribution tracking for pre-grasp planning on mobile robots. In 2022 IEEE International Conference on Robotics and Automation (ICRA) IEEE.