Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

Cherubini, Andrea; Navarro-Alarcon, David

doi:10.3389/fnbot.2020.576846

Cited by 51 publications

(27 citation statements)

References 95 publications

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“…On a more general level, the present study is related to the broader field of human-robot collaboration (Cherubini and Navarro-Alarcon, 2021). The quality of shared control depends on several factors listed by Flemisch et al (2016), such as the traceability and predictability of abilities and intents in both directions (human-machine and machine-human) as well as the arbitration of conflicts.…”

Section: Discussionmentioning

confidence: 99%

Impact of Shared Control Modalities on Performance and Usability of Semi-autonomous Prostheses

et al. 2021

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Semi-autonomous (SA) control of upper-limb prostheses can improve the performance and decrease the cognitive burden of a user. In this approach, a prosthesis is equipped with additional sensors (e.g., computer vision) that provide contextual information and enable the system to accomplish some tasks automatically. Autonomous control is fused with a volitional input of a user to compute the commands that are sent to the prosthesis. Although several promising prototypes demonstrating the potential of this approach have been presented, methods to integrate the two control streams (i.e., autonomous and volitional) have not been systematically investigated. In the present study, we implemented three shared control modalities (i.e., sequential, simultaneous, and continuous) and compared their performance, as well as the cognitive and physical burdens imposed on the user. In the sequential approach, the volitional input disabled the autonomous control. In the simultaneous approach, the volitional input to a specific degree of freedom (DoF) activated autonomous control of other DoFs, whereas in the continuous approach, autonomous control was always active except for the DoFs controlled by the user. The experiment was conducted in ten able-bodied subjects, and these subjects used an SA prosthesis to perform reach-and-grasp tasks while reacting to audio cues (dual tasking). The results demonstrated that, compared to the manual baseline (volitional control only), all three SA modalities accomplished the task in a shorter time and resulted in less volitional control input. The simultaneous SA modality performed worse than the sequential and continuous SA approaches. When systematic errors were introduced in the autonomous controller to generate a mismatch between the goals of the user and controller, the performance of SA modalities substantially decreased, even below the manual baseline. The sequential SA scheme was the least impacted one in terms of errors. The present study demonstrates that a specific approach for integrating volitional and autonomous control is indeed an important factor that significantly affects the performance and physical and cognitive load, and therefore these should be considered when designing SA prostheses.

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Section: Discussionmentioning

confidence: 99%

Impact of Shared Control Modalities on Performance and Usability of Semi-autonomous Prostheses

et al. 2021

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“…But, only the sense of touch is not enough to perform certain collaborative tasks and thus necessitates to introduce visual perception in the control framework to complement the haptics for coordinated actions [9] [10]. Combining visual and tactile perceptions for coordinated motion control requires to implement one of the three control strategies i.e, traded, hybrid and shared [11]. In traded scheme, based on the task error threshold, it switches between the visual servoing and tactile exploration.…”

Section: Introductionmentioning

confidence: 99%

Formulating Intuitive Stack-of-Tasks using Visuo-Tactile Perception for Collaborative Human-Robot Fine Manipulation

Katyara¹,

Deshpande²,

Ficuciello³

et al. 2021

Preprint

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Enabling robots to work in close proximity with humans necessitates to employ not only multi-sensory information for coordinated and autonomous interactions but also a control framework that ensures adaptive and flexible collaborative behaviour. Such a control framework needs to integrate accuracy and repeatability of robots with cognitive ability and adaptability of humans for co-manipulation. In this regard, an intuitive stack of tasks (iSoT) formulation is proposed, that defines the robot's actions based on human ergonomics and task progress. The framework is augmented with visuo-tatile perception for flexible interaction and autonomous adaption. The visual information using depth cameras, monitors and estimates the object pose and human arm gesture while the tactile feedback provides exploration skills for maintaining the desired contact to avoid slippage. Experiments conducted on robot system with human partnership for assembly and disassembly tasks confirm the effectiveness and usability of proposed framework.

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“…In last two decades, the robots have gained sufficient social trust and are extensively participating with humans in performing certain tasks that require cognitive abilities of humans to be combined with precision and strength of robots [1] [2]. However, such a social trust on robots requires to endow them with multi-sensory information especially the visuo-tactile feedback to make instant decisions, detect obstacles, recognize human intervention and adapt to varying environment proactively [3] [4]. The visuo-tactile data thus enables the robot to understand the non-verbal cues to collaborate more intuitively from human perspective.…”

Section: Introductionmentioning

confidence: 99%

Intuitive Tasks Planning Using Visuo-Tactile Perception for Human Robot Cooperation

Katyara,

Ficuciello,

Teng

et al. 2021

Preprint

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Designing robotic tasks for co-manipulation necessitates to exploit not only proprioceptive but also exteroceptive information for improved safety and autonomy. Following such instinct, this research proposes to formulate intuitive robotic tasks following human viewpoint by incorporating visuo-tactile perception. The visual data using depth cameras surveils and determines the object dimensions and human intentions while the tactile sensing ensures to maintain the desired contact to avoid slippage. Experiment performed on robot platform with human assistance under industrial settings validates the performance and applicability of proposed intuitive task formulation.

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Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

Cited by 51 publications

References 95 publications

Impact of Shared Control Modalities on Performance and Usability of Semi-autonomous Prostheses

Impact of Shared Control Modalities on Performance and Usability of Semi-autonomous Prostheses

Formulating Intuitive Stack-of-Tasks using Visuo-Tactile Perception for Collaborative Human-Robot Fine Manipulation

Intuitive Tasks Planning Using Visuo-Tactile Perception for Human Robot Cooperation

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