A Robotic Skin for Collision Avoidance and Affective Touch Recognition

Hughes, Dana; Lammie, John; Correll, Nikolaus

doi:10.1109/lra.2018.2799743

Cited by 75 publications

(52 citation statements)

References 21 publications

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“…This section describes two example robotic materials in more detail: a smart tire capable of identifying terrain for use with autonomous vehicles (Dana Hughes and Correll, 2017), and a robotic skin capable of jointly performing gesture recognition and obstacle avoidance (Hughes et al, 2018). These examples are used to demonstrate common attributes of robotic materials: processing high-bandwidth sensor information, using material-scale computing elements with limited resources, and the desire for efficient approaches to generating low-dimensional internal states or responses.…”

Section: Example Applicationsmentioning

confidence: 99%

“…A simple approach to augmenting obstacle detection in a robotic skin trained to perform gesture recognition is presented by Hughes et al (2018). The interaction of the skin patch and the environment can be represented as a probabilistic finite state machine, as shown in Figure 7.…”

Section: Example Applicationsmentioning

confidence: 99%

“…Probabilistic finite state machine used to describe and analyze the behavior of the robotic skin. Reproduced from Hughes et al (2018).…”

Section: Example Applicationsmentioning

confidence: 99%

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Materials that make robots smart

Hughes

Heckman

Correll

2019

The International Journal of Robotics Research

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We posit that embodied artificial intelligence is not only a computational, but also a materials problem. While the importance of material and structural properties in the control loop are well understood, materials can take an active role during control by tight integration of sensors, actuators, computation, and communication. We envision such materials to abstract functionality, therefore making the construction of intelligent robots more straightforward and robust. For example, robots could be made of bones that measure load, muscles that move, skin that provides the robot with information about the kind and location of tactile sensations ranging from pressure to texture and damage, eyes that extract high-level information, and brain material that provides computation in a scalable manner. Such materials will not resemble any existing engineered materials, but rather the heterogeneous components out of which their natural counterparts are made. We describe the state-of-the-art in so-called “robotic materials,” their opportunities for revolutionizing applications ranging from manipulation to autonomous driving by describing two recent robotic materials, a smart skin and a smart tire in more depth, and conclude with open challenges that the robotics community needs to address in collaboration with allies, such as wireless sensor network researchers and polymer scientists.

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Section: Example Applicationsmentioning

confidence: 99%

Section: Example Applicationsmentioning

confidence: 99%

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Materials that make robots smart

Hughes

Heckman

Correll

2019

The International Journal of Robotics Research

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“…HCRs requires sufficient safety measures to prevent damage to humans because HCRs work near humans. Several safety measures for HCRs have been proposed [1–23], some are commercially sold [7,10].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, tactile and proximity sensors have been proposed to detect an object both before and after contact using optical elements [13], capacitive measurement [14,15], and multi‐modal elements [16,17]. Previously, we have proposed the tactile and proximity sensor using a self‐capacitance measurement which can detect an object at proximity range, and contact pressure [15].…”

Section: Introductionmentioning

confidence: 99%

A General‐Purpose Safety Light Curtain Using ToF Sensor for End Effector on Human Collaborative Robot

Tsuji

Kohama

2020

IEEJ Transactions Elec Engng

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In recent years, human collaborative robots (HCRs) that work in the same space have attracted attention. HCRs with safety measures using a contact detection function are commercially sold. However, most safety measures for end effectors on HCRs are insufficient. In this paper, we propose a general-purpose safety light curtain using Time of Flight (ToF) sensors for safety measure of an end effector on HCRs. The prototype safety light curtain consists of 24 pieces of ToF sensors. ToF sensors are set on a 24 polygonal base plate, and the angle is 45 • to the end effector. The safety light curtain mounted on the top of the end effector can detect objects around the end effector without contact. Thus, the end effector on HCRs can avoid an unexpected collision using this safety light curtain. The light curtain will be used for various kinds of end effectors and works. Therefore, the safety of HCRs can be improved.

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Multi‐Modal Modular Textile Sensor for Physical Human–Robot Interaction Using Band‐Stop Filters

Kim,

Park

2023

Adv Funct Materials

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For safe coexistence between robots and humans, it is important for robots to detect the presence of nearby humans as well as any physical contacts made to its body. The design of a modular textile sensor array and an algorithm for multi‐modal sensing of human touches and other contacts with their contact forces proposed. Each sensor module in the array is capable of multi‐modal sensing, and the entire array with multiple modules requires only two wires to read the outputs from all the modules using band‐stop filter circuits. The proposed sensor system shows the structural modularity, achieved by simple fabrication of sequential lamination of conductive and non‐conductive textile materials, realizing electrical connections through conductive snap buttons that connect the modules to the circuit. The functional modularity is also achieved through the compensation algorithm, derived from the analysis of the transfer function in the frequency domain. The algorithm significantly reduces signal interferences between modules. The multi‐modality, the textile‐based design, and the structural and functional modularity of the proposed system enable practical applications to various robotic systems, including robotic skin for a collaborative robot, a wearable sensor, a robot hand sensor, and a human–computer interface, as demonstrated in this study.

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A Robotic Skin for Collision Avoidance and Affective Touch Recognition

Cited by 75 publications

References 21 publications

Materials that make robots smart

Materials that make robots smart

A General‐Purpose Safety Light Curtain Using ToF Sensor for End Effector on Human Collaborative Robot

Multi‐Modal Modular Textile Sensor for Physical Human–Robot Interaction Using Band‐Stop Filters

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