Service Robots: Trends and Technology

Gonzalez-Aguirre, Juan Angel; Osorio-Oliveros, Ricardo; Rodríguez-Hernández, Karen Lizette; Lizárraga-Iturralde, Javier; Menendez, Rubén Morales; Ramirez‐Mendoza, Ricardo A.; Ramírez-Moreno, Mauricio A.; Lozoya-Santos, Jorge de J.

doi:10.3390/app112210702

Cited by 70 publications

(66 citation statements)

References 108 publications

(132 reference statements)

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“…Along with the appearance of the era of the “artificial intelligence,” the demand for intelligent service robots is growing, and powerful robots are gradually providing more intelligent services. [ 1 ] For example, intelligent service robots can look after elderly and educate children; [ 2 ] however, intelligent service robots that live with the elderly or children must have the same perceptual capabilities as humans, such as the ability to see (sight), hear (hearing), or feel (touch) their surroundings, and these sensory abilities will allow robots to execute a variety of tasks. To accomplish these tasks, robots can focus on incorporating multiple types of sensors to sense and interpret the environment.…”

Section: Introductionmentioning

confidence: 99%

An Open‐Environment Tactile Sensing System: Toward Simple and Efficient Material Identification

et al. 2022

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Robotic perception can have simple and effective sensing functions that are unreachable for humans using only the isolated tactile perception method, with the assistance of a triboelectric nanogenerator (TENG). However, the reliability of triboelectric sensors remains a major challenge due to the inherent environmental limitations. Here, an intelligent tactile sensing system that combines a TENG and deep‐learning technology is proposed. Using a triboelectric triple tactile sensor array, typical characteristics of each testing material can be maintained stably even under different contact conditions (touch conditions and external environmental conditions) by extracting features from three independent electrical signals as well as the normalized output signals. Furthermore, a convolutional neural network model is integrated, and a high accuracy of 96.62% is achieved in a material identification task. The tactile sensing system is exhibited to an open environment for material identification and the real‐time demonstration. Compared to the complex process that humans must integrate multiple sensing (touching and viewing) to accomplish tactile perception, the proposed sensing system shows a huge advantage in cognitive learning for the visually impaired, biomimetic prosthetics, and virtual spaces construction.

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Section: Introductionmentioning

confidence: 99%

An Open‐Environment Tactile Sensing System: Toward Simple and Efficient Material Identification

et al. 2022

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“…In this sense, many researchers have tried to categorize the robots. Gonzalez-Aguirre et al [1] considered conventional robots and advanced robots working on different tasks and services. These services could include package delivery [2] and catering applications [3], among others [4,5].…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Including Social Conventions into Social Robots Navigation by Using Polygonal Triangulation and Group Asymmetric Gaussian Functions

Sousa

Barrios-Aranibar

Díaz-Amado

et al. 2022

Sensors

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Many authors have been working on approaches that can be applied to social robots to allow a more realistic/comfortable relationship between humans and robots in the same space. This paper proposes a new navigation strategy for social environments by recognizing and considering the social conventions of people and groups. To achieve that, we proposed the application of Delaunay triangulation for connecting people as vertices of a triangle network. Then, we defined a complete asymmetric Gaussian function (for individuals and groups) to decide zones where the robot must avoid passing. Furthermore, a feature generalization scheme called socialization feature was proposed to incorporate perception information that can be used to change the variance of the Gaussian function. Simulation results have been presented to demonstrate that the proposed approach can modify the path according to the perception of the robot compared to a standard A* algorithm.

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“…Mobile robotic platforms have found numerous applications over the past decade, a significant portion of which can be attributed to intralogistics and transportation in modern manufacturing, warehousing, and utility markets [1][2][3]. Although numerous sites have been automated by either automated guided vehicles (AGV) or autonomous mobile robots (AMR) with impressive deployments, the market is expected to grow by about 30% over the next five years [4,5].…”

Section: Introductionmentioning

confidence: 99%

Coordinated Multi-Robotic Vehicles Navigation and Control in Shop Floor Automation

Klančar

Seder

2022

Sensors

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In this paper, we propose a global navigation function applied to model predictive control (MPC) for autonomous mobile robots, with application to warehouse automation. The approach considers static and dynamic obstacles and generates smooth, collision-free trajectories. The navigation function is based on a potential field derived from an E* graph search algorithm on a discrete occupancy grid and by bicubic interpolation. It has convergent behavior from anywhere to the target and is computed in advance to increase computational efficiency. The novel optimization strategy used in MPC combines a discrete set of velocity candidates with randomly perturbed candidates from particle swarm optimization. Adaptive horizon length is used to improve performance. The efficiency of the proposed approaches is validated using simulations and experimental results.

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Service Robots: Trends and Technology

Cited by 70 publications

References 108 publications

An Open‐Environment Tactile Sensing System: Toward Simple and Efficient Material Identification

An Open‐Environment Tactile Sensing System: Toward Simple and Efficient Material Identification

A New Approach for Including Social Conventions into Social Robots Navigation by Using Polygonal Triangulation and Group Asymmetric Gaussian Functions

Coordinated Multi-Robotic Vehicles Navigation and Control in Shop Floor Automation

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