Contact-Aware Non-prehensile Robotic Manipulation for Object Retrieval in Cluttered Environments

The paper is accepted by IROS2023.

The source code will be released after the journal version of this paper.

You can access the pre-print version on arXiv!

Video

Abstract

Non-prehensile manipulation methods usually use a simple end effector, e.g., a single rod, to manipulate the object. Compared to the grasping method, such an end effector is compact and flexible, and hence it can perform tasks in a constrained workspace; As a trade-off, it has relatively few degrees of freedom (DoFs), resulting in an under-actuation problem with complex constraints for planning and control.

This paper proposes a new non-prehensile manipulation method for the task of object retrieval in cluttered environments, using a rod-like pusher.

Specifically, a candidate trajectory in a cluttered environment is first generated with an improved Rapidly-Exploring Random Tree (RRT) planner; Then, a Model Predictive Control (MPC) scheme is applied to stabilize the slider’s poses through necessary contact with obstacles.

Different from existing methods, the proposed approach is with the contact-aware feature, which enables the synthesized effect of active removal of obstacles, avoidance behavior, and switching contact face for improved dexterity. Hence both the feasibility and efficiency of the task are greatly promoted.

The performance of the proposed method is validated in a planar object retrieval task, where the target object, surrounded by many fixed or movable obstacles, is manipulated and isolated. Both simulation and experimental results are presented.

Contact

If you have any question, feel free to contact the authors: Yongpeng Jiang, jiangyp19@gmail.com .

Yongpeng Jiang’s Homepage is at director-of-g.github.io.