[論文レビュー] PAPRAS: Plug-And-Play Robotic Arm System

Joohyung Kim, Dhruv C Mathur+2 more|arXiv (Cornell University)|Feb 19, 2023

Advanced Manufacturing and Logistics Optimization被引用数 13

ひとこと要約

PAPRAS は、キッチン、コーヒー作り、モビリティ、スーツアップ作業でデモンストレーションされた、低遅延のマルチエージェント制御のためのドッキングマウントとオープンソースソフトウェアを備えた、軽量・モジュラー・プラグアンドプレイのロボットアームシステムです。

ABSTRACT

This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking mount(s), and software architecture including a control system. By analyzing the target task spaces at home, the dimensions and configuration of PAPRAS are determined. PAPRAS's arm is light (less than 6kg) with an optimized 3D-printed structure, and it has a high payload (3kg) as a human-arm-sized manipulator. A locking mechanism is embedded in the structure for better portability and the 3D-printed docking mount can be installed easily. PAPRAS's software architecture is developed on an open-source framework and optimized for low-latency multiagent-based distributed manipulator control. A process to create new demonstrations is presented to show PAPRAS's ease of use and efficiency. In the paper, simulations and hardware experiments are presented in various demonstrations, including sink-to-dishwasher manipulation, coffee making, mobile manipulation on a quadruped, and suit-up demo to validate the hardware and software design.

研究の動機と目的

• Design a portable, lightweight, high-payload robotic arm suitable for home/human-robot collaboration.
• Develop a modular docking system enabling plug-and-play deployment and easy portability.
• Create an open-source software architecture optimized for low-latency, multi-agent distributed control.
• Validate hardware and software through simulations and real-world demonstrations in kitchen tasks, coffee making, mobile manipulation, and assistive dressing.

提案手法

• Modify OpenMANIPULATOR-P to create a 6-DoF arm with two variants (short and long) optimized for task spaces around a kitchen table and sink.
• Implement a docking mechanism with male/female sections and locking to enable plug-and-play mounts and portability.
• Employ lightweight, 3D-printed links and topology optimization to reduce weight while maintaining stiffness and payload.
• Develop an open-source ROS Noetic-based software architecture with a global parameter server, perception, planning, control, and hardware interfaces.
• Use a low-latency distributed control framework enabling multiple arms to be controlled from a single or multiple host machines.
• Integrate perception (DOPE, OpenPose), planning (MoveIt, TRAC-IK, OMPL), and simulation (Gazebo) to enable autonomous manipulation and task demonstrations.

Figure 1 : PAPRAS mounted in various environments using the plug-and-play feature and executing manipulation tasks.

実験結果

リサーチクエスチョン

• RQ1 How can a portable, plug-and-play robotic arm system be designed to operate safely and effectively in home environments?
• RQ2 Can docking mounts and lightweight 3D-printed links maintain sufficient payload while ensuring portability?
• RQ3 Does the integrated software stack enable low-latency, multi-agent manipulation across distributed computing units?
• RQ4 Can PAPRAS perform varied demonstrations (sink-to-dishwasher, coffee making, quadruped mobile manipulation, suit-up) to validate hardware and software integration?

主な発見

• The PAPRAS arm weighs around 4.77–4.89 kg with a payload of 2.5–3 kg depending on version.
• A 6-DoF OpenMANIPULATOR-P based design with 800–900 mm reach satisfies the task space requirements for kitchen and dishwashing tasks.
• Topology optimization and 3D printing reduce link weights (Link 2: 644.0 g to 231.9 g; Link 3: 496.0 g to 211.6 g; Link 5: 114.0 g to 35.7 g) while maintaining stiffness.
• The docking mount enables easy locking/unlocking of the arm, facilitating plug-and-play deployment and portability.
• The software stack on ROS Noetic supports low-latency multi-agent control, perception, planning, and simulation, enabling demonstrations from sink to dishwasher, coffee making, and dressing tasks.
• Hardware experiments validated payload handling and motion planning in a kitchen environment.

(a) Table (top)