Towards Intelligent Pick and Place Assembly of Individualized Products Using Reinforcement Learning
TH Köln – University of Applied Sciences（科隆应用技术大学）；Cologne Cobots Lab（科隆协作机器人实验室）；Laboratory of Manufacturing Systems（制造系统实验室）；Institute of Telecommunications Technology（电信技术研究所）
Caterina Neef, Dario Luipers, Jan Bollenbacher, Christian Gebel, Anja Richert
Individualized manufacturing is becoming an important approach as a means to fulfill increasingly diverse and specific consumer requirements and expectations. While there are various solutions to the implementation of the manufacturing process, such as additive manufacturing, the subsequent automated assembly remains a challenging task. As an approach to this problem, we aim to teach a collaborative robot to successfully perform pick and place tasks by implementing reinforcement learning. For the assembly of an individualized product in a constantly changing manufacturing environment, the simulated geometric and dynamic parameters will be varied. Using reinforcement learning algorithms capable of meta-learning, the tasks will first be trained in simulation. They will then be performed in a real-world environment where new factors are introduced that were not simulated in training to confirm the robustness of the algorithms. The robot will gain its input data from tactile sensors, area scan cameras, and 3D cameras used to generate heightmaps of the environment and the objects. The selection of machine learning algorithms and hardware components as well as further research questions to realize the outlined production scenario are the results of the presented work.
Istituto Italiano di Tecnologia（意大利技术研究院）；Politecnico di Milano（米兰理工大学）
Human-robot collaborative assembly systems enhance the efficiency and productivity of the workplace but may increase the workers' cognitive demand. This paper proposes an online and quantitative framework to assess the cognitive workload induced by the interaction with a co-worker, either a human operator or an industrial collaborative robot with different control strategies. The approach monitors the operator's attention distribution and upper-body kinematics benefiting from the input images of a low-cost stereo camera and cutting-edge artificial intelligence algorithms (i.e. head pose estima…
OMRON SINIC X Corp.（欧姆龙 SINIC X 公司）；University of Southern Denmark（南丹麦大学）；Technical University Berlin（柏林工业大学）；University of Colorado Boulder（科罗拉多大学博尔德分校）；Robotic Materials Inc.（机器人材料公司）；Osaka University（大阪大学）；Kanazawa University（金泽大学）
The Industrial Assembly Challenge at the World Robot Summit was held in 2018 to showcase the state-of-the-art of autonomous manufacturing systems. The challenge included various tasks, such as bin picking, kitting, and assembly of standard industrial parts into 2D and 3D assemblies. Some of the tasks were only revealed at the competition itself, representing the challenge of "level 5" automation, i. e., programming and setting up an autonomous assembly system in less than one day. We conducted a survey among the teams that participated in the challenge and investigated aspects such as team com…
Osaka University（大阪大学）；National Inst. of AIST（日本产业技术综合研究所）
This paper proposes a novel robotic hand design for assembly tasks. The idea is to combine two simple grippers -- an inner gripper which is used for precise alignment, and an outer gripper which is used for stable holding. Conventional robotic hands require complicated compliant mechanisms or complicated control strategy and force sensing to conduct assemble tasks, which makes them costly and difficult to pick and arrange small objects like screws or washers. Compared to the conventional hands, the proposed design provides a low-cost solution for aligning, picking up, and arranging various obj…
Google Research（谷歌研究院）；Carnegie Mellon University（卡内基梅隆大学）
Most successes in robotic manipulation have been restricted to single-arm gripper robots, whose low dexterity limits the range of solvable tasks to pick-and-place, inser-tion, and object rearrangement. More complex tasks such as assembly require dual and multi-arm platforms, but entail a suite of unique challenges such as bi-arm coordination and collision avoidance, robust grasping, and long-horizon planning. In this work we investigate the feasibility of training deep reinforcement learning (RL) policies in simulation and transferring them to the real world (Sim2Real) as a generic methodology…
Johns Hopkins University（约翰斯·霍普金斯大学）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）
How can we enable users to create effective, perception-driven task plans for collaborative robots? We conducted a 35-person user study with the Behavior Tree-based CoSTAR system to determine which strategies for end user creation of generalizable robot task plans are most usable and effective. CoSTAR allows domain experts to author complex, perceptually grounded task plans for collaborative robots. As a part of CoSTAR's wide range of capabilities, it allows users to specify SmartMoves: abstract goals such as "pick up component A from the right side of the table." Users were asked to perform p…
Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning
Eindhoven University of Technology（埃因霍温理工大学）；University of Victoria（维多利亚大学）；Natural Sciences and Engineering Research Council (NSERC) Canada（加拿大自然科学与工程研究委员会）
Johns Hopkins University（约翰斯·霍普金斯大学）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）
How can we enable novice users to create effective task plans for collaborative robots? Must there be a tradeoff between generalizability and ease of use? To answer these questions, we conducted a user study with the CoSTAR system, which integrates perception and reasoning into a Behavior Tree-based task plan editor. In our study, we ask novice users to perform simple pick-and-place assembly tasks under varying perception and planning capabilities. Our study shows that users found Behavior Trees to be an effective way of specifying task plans. Furthermore, users were also able to more quickly,…
OMRON SINIC X Corp.（欧姆龙SINIC X公司）；OMRON Corp.（欧姆龙公司）；Osaka University（大阪大学）；SenseTime Japan Ltd.（商汤日本有限公司）；National Inst. of Advanced Industrial Science and Technology (AIST)（国立先进工业科学技术研究所（AIST））；Laboro.AI Inc.（Laboro.AI公司）
We propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as screwing and suctioning. A third gripper is used as a precision picking and centering tool, and uses in-built passive compliance to compensate for small position errors and uncertainty. A novel grasp point detection for bin picking is described for the kitting task, using a single depth map. Using the proposed system we competed in the Assembly Challenge of t…
Osaka University（大阪大学）；University of California, Santa Cruz（加州大学圣克鲁兹分校）
This paper develops a robotic manipulation planner for human-robot collaborative assembly. Unlike previous methods which study an independent and fully AI-equipped autonomous system, this paper explores the subtask distribution between a robot and a human and studies a human-in-the-loop robotic system for collaborative assembly. The system distributes the subtasks of an assembly to robots and humans by exploiting their advantages and avoiding their disadvantages. The robot in the system will work on pick-and-place tasks and provide workpieces to humans. The human collaborator will work on fine…
Recently, human-robot interaction (HRI) is an extensive research topic and theme which gained importance and significance. HRI aims at the complementary combination between the robot capabilities and human skills. The robots assist humans in terms of precision, speed, and force. The humans contribute in terms of the experience, knowledge of executing the task, intuition, and easy adaptation and learning, and understanding of control strategies. In this work, the applications of human-robot interaction are reviewed. These applications could be industrial, medical, agricultural, servical, and ed…
Rutgers, the State University of New Jersey（罗格斯新泽西州立大学）
Robotic pick-and-place (PnP) operations on moving conveyors find a wide range of industrial applications. In practice, simple greedy heuristics (e.g., prioritization based on the time to process a single object) are applied that achieve reasonable efficiency. We show analytically that, under a simplified telescoping robot model, these greedy approaches do not ensure time optimality of PnP operations. To address the shortcomings of classical solutions, we develop algorithms that compute optimal object picking sequences for a predetermined finite horizon. Employing dynamic programming techniques…
Centre for Mechanical Engineering, Materials and Processes (CEMMPRE)（机械工程、材料与工艺中心（CEMMPRE））；University of Coimbra（科英布拉大学）
Collaborative robots are increasingly present in industry to support human activities. However, to make the human-robot collaborative process more effective, there are several challenges to be addressed. Collaborative robotic systems need to be aware of the human activities to (1) anticipate collaborative/assistive actions, (2) learn by demonstration, and (3) activate safety procedures in shared workspace. This study proposes an action classification system to recognize primitive assembly tasks from human motion events data captured by a Dynamic and Active-pixel Vision Sensor (DAVIS). Several …
Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；The Chinese University of Hong Kong（香港中文大学）
In industry assembly lines, parts feeding machines are widely employed as the prologue of the whole procedure. They play the role of sorting the parts randomly placed in bins to the state with specified pose. With the help of the parts feeding machines, the subsequent assembly processes by robot arm can always start from the same condition. Thus it is expected that function of parting feeding machine and the robotic assembly can be integrated with one robot arm. This scheme can provide great flexibility and can also contribute to reduce the cost. The difficulties involved in this scheme lie in…
Multi-Robot Assembly of Deformable Linear Objects Using Multi-Modal Perception
Chair of Robotics, Artificial Intelligence and Real-time Systems, School of Computation, Information and Technology（机器人学、人工智能与实时系统教授会，计算、信息与技术学院）；Institute for Machine Tools and Industrial Management, School of Engineering and Design（机械加工与工业管理研究所，工程与设计学院）
IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality
University of Southern California（南加州大学）；Stanford University（斯坦福大学）；NVIDIA Corporation（英伟达公司）；University of Sydney（悉尼大学）；University of Washington（华盛顿大学）
the University of Hong Kong（香港大学）；the City University of Hong Kong（香港城市大学）；National Institute of Advanced Industrial Science and Technology (AIST)（日本产业技术综合研究所（AIST））
Pick-and-place regrasp is an important manipulation skill for a robot. It helps a robot accomplish tasks that cannot be achieved within a single grasp, due to constraints such as kinematics or collisions between the robot and the environment. Previous work on pick-and-place regrasp only leveraged flat surfaces for intermediate placements, and thus is limited in the capability to reorient an object. In this paper, we extend the reorientation capability of a pick-and-place regrasp by adding a vertical pin on the working surface and using it as the intermediate location for regrasping. In particu…
A Mosquito Pick-and-Place System for PfSPZ-based Malaria Vaccine Production
Johns Hopkins University（约翰斯·霍普金斯大学）；Georgia Tech（佐治亚理工学院）；Accenture（埃森哲）；Auris Health（奥里斯健康）；Technical University of Munich（慕尼黑工业大学）；National University of Singapore（新加坡国立大学）；Sanaria, Inc.（萨纳利亚公司）
For embodied agents, navigation is an important ability but not an isolated goal. Agents are also expected to perform specific tasks after reaching the target location, such as picking up objects and assembling them into a particular arrangement. We combine Vision-and-Language Navigation, assembling of collected objects, and object referring expression comprehension, to create a novel joint navigation-and-assembly task, named ArraMon. During this task, the agent (similar to a PokeMON GO player) is asked to find and collect different target objects one-by-one by navigating based on natural lang…
Computer Science and Artificial Intelligence Lab（计算机科学与人工智能实验室）
Expensive specialized systems have hampered development of telerobotic systems for manufacturing systems. In this paper we demonstrate a telerobotic system which can reduce the cost of such system by leveraging commercial virtual reality(VR) technology and integrating it with existing robotics control software. The system runs on a commercial gaming engine using off the shelf VR hardware. This system can be deployed on multiple network architectures from a wired local network to a wireless network connection over the Internet. The system is based on the homunculus model of mind wherein we embe…
