A Teleoperation Interface for Loco-Manipulation Control of Mobile Collaborative Robotic Assistant

2020 IEEE International Conference on Robotics and Automation (ICRA)

et al. 2020

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In this paper, a novel human-robot collaborative framework for mixed case palletizing is presented. The framework addresses several challenges associated with the detection and localisation of boxes and pallets through visual perception algorithms, high-level optimisation of the collaborative effort through effective role-allocation principles, and maximisation of packing density. A graphical user interface (GUI) is additionally developed to ensure an intuitive allocation of roles and the optimal placement of the boxes on target pallets. The framework is evaluated in two conditions where humans operate with and without the support of a Mobile COllaborative robotic Assistant (MOCA). The results show that the optimised placement can improve up to the 20% with respect to a manual execution of the same task, and reveal the high potential of MOCA in increasing the performance of collaborative palletizing tasks.

Section: A Moca: Platform and Controlmentioning

confidence: 99%

Section: A Moca: Platform and Controlmentioning

confidence: 99%

Towards an Intelligent Collaborative Robotic System for Mixed Case Palletizing

Lamon

Mattia

2020 IEEE International Conference on Robotics and Automation (ICRA)

et al. 2020

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“…The core component of the robot hardware in this paper is the new versatile cobot platform MOCA as shown in Fig. 2 that we recently presented in [19]. We additionally developed a new admittance interface, which is positioned between the robotic arm and the SoftHand.…”

Section: Mobile Collaborative Robotic Assistant (Moca)mentioning

confidence: 99%

“…wherex = x − x d is the Cartesian error from the desired task x d , and K ∈ R 6×6 and D ∈ R 6×6 are the desired Cartesian stiffness and damping matrices, respectively. Λ Λ Λ(q) ∈ R 6×6 is the Cartesian inertial and µ µ µ(q) ∈ R 6×6 the Cartesian Coriolis and centrifugal matrices, respectively (see our previous work in [19] for more details). One crucial requirement for enabling intuitive human-MOCA conjoined actions is to be able to selectively assign larger mobility to the arm or the mobile base when a desired trajectory is executed at the end-effector.…”

Section: B Whole-body Impedance Controllermentioning

confidence: 99%

MOCA-MAN: A MObile and reconfigurable Collaborative Robot Assistant for conjoined huMAN-robot actions

2020 IEEE International Conference on Robotics and Automation (ICRA)

Balatti

Lamon

et al. 2020

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The objective of this paper is to create a new collaborative robotic system that subsumes the advantages of mobile manipulators and supernumerary limbs. By exploiting the reconfiguration potential of a MObile Collaborative robot Assistant (MOCA), we create a collaborative robot that can function autonomously, in close proximity to humans, or be physically coupled to the human counterpart as a supernumerary body (MOCA-MAN). Through an admittance interface and a hand gesture recognition system, the controller can give higher priority to the mobile base (e.g., for long distance cocarrying tasks) or the arm movements (e.g., for manipulating tools), when performing conjoined actions. The resulting system has a high potential not only to reduce waste associated with the equipment waiting and setup times, but also to mitigate the human effort when performing heavy or prolonged manipulation tasks. The performance of the proposed system, i.e., MOCA-MAN, is evaluated by multiple subjects in two different use-case scenarios, which require large mobility or close-proximity manipulation.

“…MOCA [16] is a new versatile research robotic platform, designed for advanced research on human-robot interaction and collaboration, with potential applications in flexible manufacturing scenarios. Three commercial components are assembled to build it: a Panda robotic arm by Franka Emika, equipped with the underactuated Pisa/IIT SoftHand [17], that are mounted on top of a SUMMIT-XL STEEL mobile platform by Robotnik.…”

Section: A Moca Control Modulementioning

confidence: 99%

Towards Ergonomic Control of Collaborative Effort in Multi-human Mobile-robot Teams

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Lorenzini

Balatti

et al. 2019

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In this paper, we propose a control framework for a multi-human and mobile-robot collaborative team, that takes into account the co-workers' ergonomic requirements as well as the demand for high flexibility in the manufacturing industries. The new MObile Collaborative robotic Assistant (MOCA), which is composed of a lightweight manipulator arm, an underactuated hand, and a mobile platform driven by four omni-directional wheels enabling mobility in the workspace, is able to accomplish multiple tasks in a wide area with a high level of adaptability. In addition, an ergonomics module to anticipate and mitigate the human risk factors by means of a multi-object optimisation is integrated into the framework to ensure human safety and improvement of working conditions. The main advantage of this approach is that MOCA can assist multiple human operators, reducing their physical risks, with fast-adaptive capacities due to agile mobility and advanced interaction and manipulation. We validated the proposed method with an experiment simulating a simple manufacturing line which involves two subjects and the MOCA. The results demonstrate that the proposed framework is able to address multi-workers' ergonomics with a high level of flexibility in the workplace.