A Multi-modal Sensor Array for Safe Human-Robot Interaction and Mapping

Abah, Colette; Orekhov, Andrew L.; Johnston, Garrison L.H.; Yin, Peng; Choset, Howie; Simaan, Nabil

doi:10.1109/icra.2019.8793466

Cited by 11 publications

(6 citation statements)

References 22 publications

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“…This causes the light emitted from the optical fiber to travel a smaller distance, hence detecting contact with an object. Another approach of using a sensory array is presented in [ 67 ]. In this case, the authors proposed a continuum robot consisting of multiple segments (see Figure 8 b).…”

Section: Classificationmentioning

confidence: 99%

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Sensing of Continuum Robots: A Review

Sincak,

Prada,

Miková

et al. 2024

Sensors

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The field of continuum robotics is rapidly developing. The development of new kinematic structures, locomotion principles and control strategies is driving the development of new types of sensors and sensing methodologies. The sensing in continuum robots can be divided into shape perception and environment perception. The environment perception is focusing on sensing the interactions between the robot and environment. These sensors are often embedded on an outer layer of the robots, so the interactions can be detected. The shape perception is sensing the robot’s shape using various principles. There are three main groups of sensors that use the properties of electricity, magnetism and optics to measure the shape of the continuum robots. The sensors based on measuring the properties of electricity are often based on measuring the electrical resistance or capacitance of the flexible sensor. Sensors based on magnetism use properties of permanent magnets or coils that are attached to the robot. Their magnetic field, flux or other properties are then tracked, and shape reconstruction can be performed. The last group of sensors is mostly based on leveraging the properties of traveling light through optical fibers. There are multiple objectives of this work. Objective number one is to clearly categorize the sensors and make a clear distinction between them. Objective number two is to determine the trend and progress of the sensors used in continuum robotics. And finally, the third objective is to define the challenges that the researchers are currently facing. The challenges of sensing the shape or the interaction with the environment of continuum robots are currently in the miniaturization of existing sensors and the development of novel sensing methods.

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Section: Classificationmentioning

confidence: 99%

“…The application of environment sensors is showcased in [ 64 , 67 ]. In this study, the authors proposed a custom continuum robot arm, made of discs containing environment sensors ( Figure 12 ).…”

Section: Classificationmentioning

confidence: 99%

Sensing of Continuum Robots: A Review

Sincak,

Prada,

Miková

et al. 2024

Sensors

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“…A continuum robot can tune its stiffness by varying its diameter with a reconfigurable mechanism; [ 75 ] locking tendons along the backbone; [ 76 ] integrating a movable stiffer element into the backbone; [ 77,78 ] or exploiting an anisotropic distribution of the flexural stiffness of the structure. [ 79 ]…”

Section: Designmentioning

confidence: 99%

Continuum Robots: An Overview

Russo

Sadati

Dong

et al. 2023

Advanced Intelligent Systems

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When thinking of robots, the image that immediately springs to mind is either an android, designed to resemble human beings and mimic their behavior, or an industrial manipulator, for example, a large machine of rigid steel working in an assembly line. However, robotic systems of multiple forms have been developed to carry out the most diverse tasks, with designs that evolved from readily available structures, such as vehicles, or inspired by nature. In the last decade, more and more bioinspired designs have been enabled by advances in computer science, materials, and manufacturing. Among them, continuum robots, inspired by snakes, trunks, and tendrils, are characterized by a compliant backbone capable of continuous bending, whose shape (configuration, i.e., position and orientation along the backbone curve) is controlled by applying loads through onboard "intrinsic" actuators (e.g., pneumatics or hydraulics) or transmission elements (e.g., tendons, rods, or compliant tubes) that are pushed/pulled from an extremity of the backbone ("extrinsic actuation"). These robots have flexible bodies with a high length to cross-section diameter ratio and are uniquely suited to tasks that require the deployment of tools or sensors with a long reach into tortuous and narrow paths. [1] Continuum robots were first developed in the 1960s [2] and rose to prominence in the late 1990s, [3] when they were often called elephant trunk, [4] tentacle/tendril, [5] or flexible [6] manipulators. Whereas other robots were characterized by intrinsic actuation and larger sizes, research on continuum robots first focused on miniaturization for medical applications, [7,8] leading to extrinsic actuation to enable leaner designs. Recently, continuum robots have been developed for a wider range of applications, including manufacturing, aerospace, search and rescue, and nuclear. In such scenarios, the infinite degrees of freedom (DoFs) of these slender robots enable inspection and intervention in areas that cannot be accessed by conventional robots (e.g., tunnels [9] and gas turbines [10] ).An exhaustive literature search (see Appendix) outlines a surging interest in continuum robots, with a 19.6% average annual growth in publications between 2012 and 2021 (continuum robot search on Web of Science). Three main topics can be observed in recent literature surveys, listed in Table 1. DesignTendon-driven and concentric tube robots are predominant in surveys, but they are not the only design solutions. [18] This richer literature can be attributed to intense research effort toward medical and other small-scale applications when compared to larger-scale tasks (e.g., manipulation) where intrinsic actuation is advantageous.

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“…Finally, it is worth mentioning the work described in [ 84 ], where a multi-modal sensor array for safe human–robot interaction and mapping is presented. The sensor array consists of ST Micro-electronic VL6180X Time-of-Flight (ToF) sensors (which measure the time the light needs to travel to an object and back to the sensor) and Triaxis magnetic-field sensors (MLX90393) for force sensing and localized contact detection.…”

Section: Related Workmentioning

confidence: 99%

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

Fraga‐Lamas

Barros

Lopes

et al. 2022

Sensors

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While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.

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A Multi-modal Sensor Array for Safe Human-Robot Interaction and Mapping

Cited by 11 publications

References 22 publications

Sensing of Continuum Robots: A Review

Sensing of Continuum Robots: A Review

Continuum Robots: An Overview

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

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