Human-in-the-Loop Robotic Manipulation Planning for Collaborative Assembly

Raessa, Mohamed; Chen, Jimmy Chi Yin; Wan, Weiwei; Harada, Kensuke

doi:10.1109/tase.2020.2978917

Cited by 50 publications

(26 citation statements)

References 57 publications

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“…In particular, the human adaptability to biological and non-biological velocity profiles during an elliptic movement are examined, showing that a robot control oriented to the biological velocity profiles increases the physical ergonomics for the operator. Similarly, [94] -which mainly aims at improving the efficiency of the assembly process-focuses on the motion planning problem aiming at optimizing the handover between robot and human in the ergonomics perspective.…”

Section: A Motion Planningmentioning

confidence: 99%

Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey

Proia

Carli

Cavone

et al. 2022

IEEE Trans. Automat. Sci. Eng.

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The fourth industrial revolution, also known as Industry 4.0, is reshaping the way individuals live and work while providing a substantial influence on the manufacturing scenario.The key enabling technology that has made Industry 4.0 a concrete reality is without doubt collaborative robotics, which is also evolving as a fundamental pillar of the next revolution, the so-called Industry 5.0. The improvement of employees' safety and well-being, together with the increase of profitability and productivity, are indeed the main goals of human-robot collaboration (HRC) in the industrial setting. The robotic controller design and the analysis of existing decision and control techniques are crucially needed to develop innovative models and state-of-the-art methodologies for a safe, ergonomic, and efficient HRC. To this aim, this paper presents an accurate review of the most recent and relevant contributions to the related literature, focusing on the control perspective. All the surveyed works are carefully selected and categorized by target (i.e., safety, ergonomics, and efficiency), and then by problem and type of control, in presence or absence of optimization. Finally, the discussion of the achieved results and the analysis of the emerging challenges in this research field are reported, highlighting the identified gaps and the promising future developments in the context of the digital evolution.Note to Practitioners-The design and development of manufacturing systems are experiencing substantial changes towards full automation. This ongoing challenge is being tackled by academia and industrial practitioners with the adoption of collaborative robots, where the skills and peculiarities of humans (e.g., intelligence, creativity, adaptability, etc.) and robots (e.g., flexibility, pinpoint accuracy, tirelessness, etc.) are combined to better perform a variety of tasks. Nevertheless, due to their different characteristics, there is an emerging need for designing suitable decision and control techniques to ensure a safe and ergonomic HRC, while keeping the highest level of productivity. Against this background, the aim of this paper is to provide researchers and practitioners with a reference source in the related field, which can help them designing and developing suitable solutions to control problems in safe, ergonomic, and efficient collaborative robotics.

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Section: A Motion Planningmentioning

confidence: 99%

Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey

Proia

Carli

Cavone

et al. 2022

IEEE Trans. Automat. Sci. Eng.

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show abstract

“…It should be noticed that some specific characteristics of current robot skin are outperformed natural skin to some extent. For example, Wang et al [78] developed a pressure-sensitive skin that has a spatial resolution of 347 per centimeter 2 . A comprehensive investigation of each sensing modality of recent advancements in robot skin is summarized in the following sections one by one.…”

Section: The State-of-the-artmentioning

confidence: 99%

“…As an existing system with general-purpose, portable, and ready-to-deploy hardware modules, cobots can address fluctuations of application scenarios in demand on whether the cobot is collaborative, teleoperated, or autonomous, i.e., the three operating modalities of cobots. This distinguishing feature is extending their applications from the conventional production line to a more diverse range of human-centered scenarios [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Review of Robot Skin: A Potential Enabler for Safe Collaboration, Immersive Teleoperation, and Affective Interaction of Future Collaborative Robots

Pang

Yang

Pang

2021

IEEE Trans. Med. Robot. Bionics

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The emerging applications of collaborative robots (cobots) are spilling out from product manufactories to service industries for human care, such as patient care for combating the coronavirus disease 2019 (COVID-19) pandemic and in-home care for coping with the aging society. There are urgent demands on equipping cobots with safe collaboration, immersive teleoperation, affective interaction, and other features (e.g., energy autonomy and self-learning) to make cobots capable of these application scenarios. Robot skin, as a potential enabler, is able to boost the development of cobots to address these distinguishing features from the perspective of multimodal sensing and self-contained actuation. This review introduces the potential applications of cobots for human care together with those demanded features. In addition, the explicit roles of robot skin in satisfying the escalating demands of those features on inherent safety, sensory feedback, natural interaction, and energy autonomy are analyzed. Furthermore, a comprehensive review of the recent progress in functionalized robot skin in components level, including proximity, pressure, temperature, sensory feedback, and stiffness tuning, is presented. Results show that the codesign of these sensing and actuation functionalities may enable robot skin to provide improved safety, intuitive feedback, and natural interfaces for future cobots in human care applications. Finally, open challenges and future directions in the real implementation of robot skin and its system synthesis are presented and discussed.

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“…When a two-finger parallel gripper manipulates long and heavy objects, they become prone to slippage in-hand (or drooping) due to the effect of gravity torque. The gravitational torque determines the drooping motion and the gripper’s frictional torque (Raessa et al , 2020). When a parallel gripper gets inclined, the gravitational torque around the jaw opening direction increases.…”

Section: Constrained Drooping and Grasp Transition Criterionmentioning

confidence: 99%

“…The earliest studies worked on drooping manipulation are Aiyama et al (1993) and Carlisle et al (1994). In our previous research (Raessa et al , 2020), we examined the reasons behind the drooping motion associated with heavy objects manipulation and implemented a constrained motion planner to eliminate it. In this paper, we take advantage of our understanding about the drooping to transit grasp poses and realize in-hand pose adjustment.…”

Section: Introductionmentioning

confidence: 99%

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

Raessa

Wan

Harada

2021

Self Cite

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Purpose This paper aims to present a hierarchical motion planner for planning the manipulation motion to repose long and heavy objects considering external support surfaces. Design/methodology/approach The planner includes a task-level layer and a motion-level layer. This paper formulates the manipulation planning problem at the task level by considering grasp poses as nodes and object poses for edges. This paper considers regrasping and constrained in-hand slip (drooping) during building graphs and find mixed regrasping and drooping sequences by searching the graph. The generated sequences autonomously divide the object weight between the arm and the support surface and avoid configuration obstacles. Cartesian planning is used at the robot motion level to generate motions between adjacent critical grasp poses of the sequence found by the task-level layer. Findings Various experiments are carried out to examine the performance of the proposed planner. The results show improved capability of robot arms to manipulate long and heavy objects using the proposed planner. Originality/value The authors’ contribution is that they initially develop a graph-based planning system that reasons both in-hand and regrasp manipulation motion considering external supports. On one hand, the planner integrates regrasping and drooping to realize in-hand manipulation with external support. On the other hand, it switches states by releasing and regrasping objects when the object is in stably placed. The search graphs' nodes could be retrieved from remote cloud servers that provide a large amount of pre-annotated data to implement cyber intelligence.

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Human-in-the-Loop Robotic Manipulation Planning for Collaborative Assembly

Cited by 50 publications

References 57 publications

Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey

Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey

Review of Robot Skin: A Potential Enabler for Safe Collaboration, Immersive Teleoperation, and Affective Interaction of Future Collaborative Robots

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

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