Active haptic perception in robots: a review

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Active haptic perception in robots: a review. / Seminara, Lucia; Gastaldo, Paulo; Watt, Simon J. et al.
Yn: Frontiers in Neurorobotics, Cyfrol 13, 53, 17.07.2019.

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

HarvardHarvard

Seminara, L, Gastaldo, P, Watt, SJ, Valyear, KF, Zuher, F & Mastrogiovanni, F 2019, 'Active haptic perception in robots: a review', Frontiers in Neurorobotics, cyfrol. 13, 53. https://doi.org/10.3389/fnbot.2019.00053

APA

Seminara, L., Gastaldo, P., Watt, S. J., Valyear, K. F., Zuher, F., & Mastrogiovanni, F. (2019). Active haptic perception in robots: a review. Frontiers in Neurorobotics, 13, Erthygl 53. https://doi.org/10.3389/fnbot.2019.00053

CBE

Seminara L, Gastaldo P, Watt SJ, Valyear KF, Zuher F, Mastrogiovanni F. 2019. Active haptic perception in robots: a review. Frontiers in Neurorobotics. 13:Article 53. https://doi.org/10.3389/fnbot.2019.00053

MLA

Seminara, Lucia et al. "Active haptic perception in robots: a review". Frontiers in Neurorobotics. 2019. 13. https://doi.org/10.3389/fnbot.2019.00053

VancouverVancouver

Seminara L, Gastaldo P, Watt SJ, Valyear KF, Zuher F, Mastrogiovanni F. Active haptic perception in robots: a review. Frontiers in Neurorobotics. 2019 Gor 17;13:53. doi: 10.3389/fnbot.2019.00053

Author

Seminara, Lucia ; Gastaldo, Paulo ; Watt, Simon J. et al. / Active haptic perception in robots: a review. Yn: Frontiers in Neurorobotics. 2019 ; Cyfrol 13.

RIS

TY - JOUR

T1 - Active haptic perception in robots: a review

AU - Seminara, Lucia

AU - Gastaldo, Paulo

AU - Watt, Simon J.

AU - Valyear, Kenneth F.

AU - Zuher, Fernando

AU - Mastrogiovanni, Fulvio

PY - 2019/7/17

Y1 - 2019/7/17

N2 - In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed. In all these contexts, robots are requested to perform tasks within open-ended conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm in the design of robots: on-line and safe feedback motion control becomes the core of modern robot systems. Future robots will learn autonomously, interact safely and possess qualities like self-maintenance. Attaining these features would have been relatively easy if a complete model of the environment was available, and if the robot actuators could execute motion commands perfectly relative to this model. Unfortunately, a complete world model is not available and robots have to plan and execute the tasks in the presence of environmental uncertainties which makes sensing an important component of new generation robots. For this reason, today's new generation robots are equipped with more and more sensing components, and consequently they are ready to actively deal with the high complexity of the real world. Complex sensorimotor tasks such as exploration require coordination between the motor system and the sensory feedback. For robot control purposes, sensory feedback should be adequately organized in terms of relevant features and the associated data representation. In this paper, we propose an overall functional picture linking sensing to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic qualities of haptic perception in humans inspire the models and categories comprising the proposed classification. The objective is to provide a reasoned, principled perspective on the connections between different taxonomies used in the Robotics and human haptic literature. The specific case of active exploration is chosen to ground interesting use cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has been treated only to a limited extent compared to grasping and manipulation. Second, exploration involves specific robot behaviors that exploit distributed and heterogeneous sensory data.

AB - In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed. In all these contexts, robots are requested to perform tasks within open-ended conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm in the design of robots: on-line and safe feedback motion control becomes the core of modern robot systems. Future robots will learn autonomously, interact safely and possess qualities like self-maintenance. Attaining these features would have been relatively easy if a complete model of the environment was available, and if the robot actuators could execute motion commands perfectly relative to this model. Unfortunately, a complete world model is not available and robots have to plan and execute the tasks in the presence of environmental uncertainties which makes sensing an important component of new generation robots. For this reason, today's new generation robots are equipped with more and more sensing components, and consequently they are ready to actively deal with the high complexity of the real world. Complex sensorimotor tasks such as exploration require coordination between the motor system and the sensory feedback. For robot control purposes, sensory feedback should be adequately organized in terms of relevant features and the associated data representation. In this paper, we propose an overall functional picture linking sensing to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic qualities of haptic perception in humans inspire the models and categories comprising the proposed classification. The objective is to provide a reasoned, principled perspective on the connections between different taxonomies used in the Robotics and human haptic literature. The specific case of active exploration is chosen to ground interesting use cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has been treated only to a limited extent compared to grasping and manipulation. Second, exploration involves specific robot behaviors that exploit distributed and heterogeneous sensory data.

KW - active touch

KW - exploration

KW - haptic perception

KW - humans and robots

KW - robot touch

KW - sensorimotor control

U2 - 10.3389/fnbot.2019.00053

DO - 10.3389/fnbot.2019.00053

M3 - Article

C2 - 31379549

VL - 13

JO - Frontiers in Neurorobotics

JF - Frontiers in Neurorobotics

SN - 1662-5218

M1 - 53

ER -