Techno Press
Tp_Editing System.E (TES.E)
Login Search
You logged in as

arr
 
CONTENTS
Volume 2, Number 1, March 2018
 


Abstract
To monitor the environment and determine the source of a pollutant gradient using a multiple robot swarm, we propose a hybrid algorithm that combines two bio-inspired algorithms mimicking chemotaxis and pheromones of bacteria. The algorithm is implemented in virtual robot agents in a simulator to evaluate their feasibility and efficiency in gradient maps with different sizes. Simulation results show that the chemotaxis controller guided robot agents to the locations with higher pollutant concentrations, while the pheromone marked in a virtual field increased the efficiency of the search by reducing the visiting redundancy. The number of steps required to reach the target point did not increase proportionally as the map size increased, but were less than those in the linear whole-map search method. Furthermore, the robot agents could function with simple sensor composition, minimum information about the map, and low calculation capacity.

Key Words
bio-inspired; chemotaxis; pheromone; swarm control; environmental monitoring

Address
Kyukwang Kim and Hyun Myung: Urban Robotics Laboratory(URL), Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Hyeongkeun Kim: Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology,
291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Abstract
This paper presents the performance of Teaching-Learning-Based Optimization (TLBO) algorithm for optimum static balancing of a robot manipulator. Static balancing of robot manipulator is an important aspect of the overall robot performance and the most demanding process in any robot system to match the need for the production requirements. The average force on the gripper in the working area is considered as an objective function. Length of the links, angle between them and stiffness of springs are considered as the design variables. Three robot manipulator configurations are optimized. The results show the better or competitive performance of the TLBO algorithm over the other optimization algorithms considered by the previous researchers.

Key Words
static balancing; robot manipulator; teaching-learning-based optimization algorithm

Address
R. Venkata Rao: Department of Mechanical Engineering, S.V. National Institute of Technology, Ichchanath, Surat,
Gujarat 395 007, India

Gajanan Waghmare: Department of Mechanical Engineering, Sandip Institute of Engineering and Management, Nashik, Maharashtra 422213, India

Abstract
This paper presents a novel feature detection algorithm called depth-hybrid speeded-up robust features (DH-SURF) augmented by depth information in the speeded-up robust features (SURF) algorithm. In the keypoint detection part of classical SURF, the standard deviation of the Gaussian kernel is varied for its scale-invariance property, resulting in increased computational complexity. We propose a keypoint detection method with less variation of the standard deviation by using depth data from a red-green-blue depth (RGB-D) sensor. Our approach maintains a scale-invariance property while reducing computation time. An RGB-D simultaneous localization and mapping (SLAM) system uses a feature extraction method and depth data concurrently; thus, the system is well-suited for showing the performance of the DH-SURF method. DH-SURF was implemented on a central processing unit (CPU) and a graphics processing unit (GPU), respectively, and was validated through the real-time RGB-D SLAM.

Key Words
speeded-up robust feature (SURF); depth-hybrid; red-green-blue depth (RGB-D) sensor; simultaneous localization and mapping (SLAM)

Address
Donghwa Lee: Division of Computer & Communication Engineering, Daegu University, Gyeongsan, Republic of Korea

Hyungjin Kim, Sungwook Jung and Hyun Myung: Urban Robotics Laboratory, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea


Abstract
Even though the popularity of projection mapping continues to increase and it is being implemented in more and more settings, most current projection mapping systems are limited to special purposes, such as outdoor events, live theater and musical performances. This lack of versatility arises from the large number of projectors needed and their proper calibration. Furthermore, we cannot change the positions and poses of projectors, or their projection targets, after the projectors have been calibrated. To overcome these problems, we propose a projection mapping method using a projector robot that can perform projection mapping in more general or ubiquitous situations, such as shopping malls. We can estimate a projector

Key Words
projection mapping; projector robot; multiple objects; self-localization; point cloud

Address
Hirotake Yamazoe and Joo-Ho Lee: College of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577, Japan

Misaki Kasetani and Tomonobu Noguchi: Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577, Japan

Abstract
Autonomous mobile service medical robots (AMSMRs) are one of the promising developments in contemporary medical robotics. In this study, we consider the essential technical and intellectual abilities needed by AMSMRs. Based on expert analysis of the behavior exhibited by AMSMRs in clinics under basic scenarios, these robots can be classified as intellectual dynamic systems acting according to a situation in a multi-object and multi-agent environment. An AMSMR should identify different objects that define the presented territory (rooms and paths), different objects between and inside rooms (doors, tables, and beds, among others), and other robots. They should also identify the means for interacting with these objects, people and their speech, different information for communication, and small objects for transportation. These are included in the minimum set required to form the internal world model in an AMSMR. Recognizing door handles and opening doors are some of the most difficult problems for contemporary AMSMRs. The ability to recognize the meaning of human speech and actions and to assist them effectively are other problems that need solutions. These unresolved issues indicate that AMSMRs will need to pass through some learning and training programs before starting real work in hospitals.

Key Words
medical robot; service; intellectual abilities; technical requirements; internal world model

Address
Dmitry A. Rogatkin: 1.) Laboratory of Medical and Physics Research, MONIKI named after M.F. Vladimirskiy, Shepkina str. 61/2, Moscow, 129110, Russia
2.) LLC \"R&D Center EOS-Medica\", Nauchny proezd, 8, b.1, Moscow, 117246, Russia

Evgeniy V. Velikanov: LLC \"R&D Center EOS-Medica\", Nauchny proezd, 8, b.1, Moscow, 117246, Russia

Abstract
Innovation is considered as key to ensure continuous advancement and firm progress in any field. Robotics, with no exception, has gained triumph and approval based on its strength to address divers range of applications as well as its capacity to adapt new ways and means to enhance its applicability. The core of novelty in robotics technology is the perpetual curiosity of human beings to imitate natural systems. This desire urges to continuously explore and find new feet. In the past, contemporary machines, in different shapes, sizes and capabilities, were developed that can perform variety of tasks. The major advantage of these developments was the ability to exhibit superior control, strength and repeatability than the corresponding systems they were replicating. However, these systems were rigid and composed of hard an underlying structure, which is a constraint in bringing into being the compliance that exists in natural organisms. Inspiration of achieving such compliance and to take the full advantage of the design scheme of biological systems compelled researchers and scientists to develop systems avoiding conventional rigid structures. This ambition, to produce biological duos, needs soft and more flexible materials and structures to realize innovative robotic systems. This new footpath to craft biological mockups facilitates further to exploit new materials, novel design methodologies and new control techniques. This paper presents an appraisal on such innovative comprehensions, conferring to their design specific importance. This demonstration is potentially useful to prompt the novelty of soft robotics.

Key Words
soft robotics; bio-mimicking; bio-inspiration; bio-robots; flexibility; compliance

Address
Ahmad M. Tahir, Giovanna A. Naselli and Matteo Zoppi: Department of Mechanical Engineering (DIME), PMAR Labs, University of Genoa, Genova, Italy

Abstract
The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

Key Words
PUMA robot manipulator; FPGA based PI observer; fault diagnosis; ARX method; ARX-Laguerre technique; observation fault diagnosis; PI observation technique

Address
Farzin Piltana and Jong-Myon Kim: School of Electrical Engineering, University of Ulsan, Ulsan 680-749, South Korea


Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2024 Techno-Press ALL RIGHTS RESERVED.
P.O. Box 33, Yuseong, Daejeon 34186 Korea, Email: info@techno-press.com