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Physical World Cognition for Robotic Application

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 5384

Special Issue Editors


E-Mail Website1 Website2
Guest Editor
Graduate School of Information, Production and Systems (IPS), Waseda University, Kitakyushu 808-0135, Japan
Interests: robotics; mechatronics; human–robot interaction; system integration; biorobotics; social robot; mobile robot; rehabilitation robotics; smart pedagogy; technology-enhanced learning

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Guest Editor
Institute of Micromechanics and Photonics, Mechatronics Faculty, Warsaw University of Technology, Św. A. Boboli 8, 520 room, 02-525 Warsaw, Poland
Interests: 3D/4D scanning; multi-modal and multi-directional 3D/4D scanning; 3D/4D data processing; 3D segmentation and recognition; automation of visual sensing processes; automation of 3D digitization
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Special Issue Information

Dear Colleagues,

Various systems using robotic technology are being put to practical use. Perception of the outside / external world (physical world) is the first process for performing a task in human behavior and robotic system operation.

In this Special Issue, we are calling for papers on cognition in robotic systems and applications using that cognitive function. Cognition is for judging and deciding the following action, and the action is to actualize the application in a robotic system. Therefore, cognitive function is closely related to the application. A robotic system needs to take some action to realize something, and it perceives the physical world to judge and decide its operation.

Cognition and its application in robotic systems (mechatronic systems, intelligent vehicles, etc.) are possible topics. Examples include the following topics but are not limited to them:

  • a personal robot recognizes and identifies the user's behavior to check the user's health status;
  • a robot helpmate that can learn from the environments so that it can robustly perceive dynamic environments with minimal/no human intervention;
  • a mobile service robot observes a dynamically changing indoor/outdoor environment to carry out transportation work efficiently;
  • a robot working in a retail shop recognizes an object's shape and determines its grasping method for merchandise display;
  • a self-driving car perceives the external environment so that it can continue driving in any environmental conditions with consistent reliability;
  • a drone must perceive dynamic environments and react accordingly to execute tasks and land autonomously;
  • a robotic agricultural machine needs to accurately grasp the current land conditions for automatic operation such as tilling, plowing, and fertilizer application;
  • a robotic system needs to assess the surface or object current state to influence the actual process control parameters;
  • an underwater robot to explore the deep ocean must automatically sense the environment and behave correctly in communication-limited, low-light and high-pressure situations.

Prof. Dr. Takafumi Matsumaru
Prof. Dr. Robert Sitnik
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • physical / external / outside world
  • sensation / perception/ cognition
  • judgement / decision
  • sensor fusion
  • object detection
  • shape recognition
  • human-robot interaction
  • human motion / action / behaviour
  • scene understanding
  • dynamic environmental
  • 3D/4D reconstruction
  • robotics system
  • mechatronic system
  • intelligent system
  • robot manipulator
  • mobile robot
  • service robot
  • intelligent vehicle
  • self-driving car
  • UAV (Unmanned Aerial Vehicle)
  • AUV (Autonomous Underwater Vehicle)
  • mapping and localization
  • vision sensor
  • depth camera
  • RBG-D sensor
  • range scanner
  • LiDAR (Light Imaging Detection and Ranging) / RADAR (Radio Detection and Ranging)
  • 3D/4D Point Cloud
  • IMU (Inertial Measurement Unit)
  • GPS (Global Positioning System) / GNSS (Global Navigation Satellite System)
  • supervised  control / shared autonomy
  • motion / task planning
  • Machine Learning (Machine Learning) / Deep Learning (DL) / Reinforcement Learning (RL)

Published Papers (2 papers)

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Research

21 pages, 3704 KiB  
Article
Path Planning and Motion Control of Indoor Mobile Robot under Exploration-Based SLAM (e-SLAM)
by Rohit Roy, You-Peng Tu, Long-Jye Sheu, Wei-Hua Chieng, Li-Chuan Tang and Hasan Ismail
Sensors 2023, 23(7), 3606; https://doi.org/10.3390/s23073606 - 30 Mar 2023
Cited by 3 | Viewed by 2952
Abstract
Indoor mobile robot (IMR) motion control for e-SLAM techniques with limited sensors, i.e., only LiDAR, is proposed in this research. The path was initially generated from simple floor plans constructed by the IMR exploration. The path planning starts from the vertices which can [...] Read more.
Indoor mobile robot (IMR) motion control for e-SLAM techniques with limited sensors, i.e., only LiDAR, is proposed in this research. The path was initially generated from simple floor plans constructed by the IMR exploration. The path planning starts from the vertices which can be traveled through, proceeds to the velocity planning on both cornering and linear motion, and reaches the interpolated discrete points joining the vertices. The IMR recognizes its location and environment gradually from the LiDAR data. The study imposes the upper rings of the LiDAR image to perform localization while the lower rings are for obstacle detection. The IMR must travel through a series of featured vertices and perform the path planning further generating an integrated LiDAR image. A considerable challenge is that the LiDAR data are the only source to be compared with the path planned according to the floor map. Certain changes still need to be adapted into, for example, the distance precision with relevance to the floor map and the IMR deviation in order to avoid obstacles on the path. The LiDAR setting and IMR speed regulation account for a critical issue. The study contributed to integrating a step-by-step procedure of implementing path planning and motion control using solely the LiDAR data along with the integration of various pieces of software. The control strategy is thus improved while experimenting with various proportional control gains for position, orientation, and velocity of the LiDAR in the IMR. Full article
(This article belongs to the Special Issue Physical World Cognition for Robotic Application)
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14 pages, 7286 KiB  
Article
Novel Robotic Arm Working-Area AI Protection System
by Jeng-Dao Lee, En-Shuo Jheng, Chia-Chen Kuo, Hong-Ming Chen and Ying-Hsiu Hung
Sensors 2023, 23(5), 2765; https://doi.org/10.3390/s23052765 - 02 Mar 2023
Cited by 2 | Viewed by 1909
Abstract
From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure [...] Read more.
From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on a stack light and sent through an M-JPEG streaming server so that the detected image can be displayed through the browser. According to the experimental results of this system installed on a robotic arm workstation, it is proved that it can ensure recognition reaches 97%. When a person enters the dangerous range of the working robotic arm, the arm can be stopped within about 50 ms, which will effectively improve the safety of its use. Full article
(This article belongs to the Special Issue Physical World Cognition for Robotic Application)
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