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Sheir Afgen Zaheer

Bio: Sheir Afgen Zaheer is an academic researcher from KAIST. The author has contributed to research in topics: Robot & Task (project management). The author has an hindex of 6, co-authored 11 publications receiving 127 citations. Previous affiliations of Sheir Afgen Zaheer include National University of Science and Technology.

Papers
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Journal ArticleDOI
TL;DR: The simulation results demonstrate that the proposed RODAA algorithm is capable of completing the panel cleaning mission faster than other auction-based task allocation algorithms and has lower overall resource consumption.
Abstract: This paper proposes a resource-oriented, decentralized auction algorithm (RODAA) for multirobot task allocation considering multiple resources of the robots and limited robot communication range. The resources that this paper focuses on are the expendable supplies that a robot consumes and recharges while performing tasks, such as energy. In the proposed algorithm, each robot generates its cost for the task in a probabilistic manner considering multiple paths that visit none or different combinations of refill stations for performing the task based on the robot's residual resources. For robust and time-efficient task allocation with limited robot communication range in a dynamic network, a multihop-based auction algorithm is proposed. This paper also introduces a solar panel cleaning mission as a new application for multirobot systems and the proposed algorithm is implemented in the simulation of the mission. The simulation results demonstrate that the proposed algorithm is capable of completing the panel cleaning mission faster than other auction-based task allocation algorithms and has lower overall resource consumption.

47 citations

Journal ArticleDOI
TL;DR: This classification categorizes the intelligence of robots based on the different aspects of awareness and the ability to act deliberately as a result of such awareness into six categories: cognitive intelligence, social intelligence, behavioral intelligence, ambient intelligence, collective intelligence and genetic intelligence.
Abstract: The ability to think has been one of the most fascinating features of robots in science fiction since the introduction of the word 'robot' by Karel Capek in his Czech science fiction play, known as 'Rossum's Universal Robots' in English [1]. Since Capek's first depiction in 1921, science fictionists generally portray robots as intelligent humanoid machines that are subservient to humans. Android is another term used for such robots in modern linguistics. However, the development of robots with the ability to think has largely been a fantasy for robot scientists and engineers. Nevertheless, the evolution of robots has come a long way since the first industrial robot 'Unimate' in 1954. Robots have transformed from large automated manufacturing facilities to applications in our homes and even into our pockets as software robots in our PDAs and smart phones [2], [3]. This paper classifies robot intelligence into six categories: cognitive intelligence, social intelligence, behavioral intelligence, ambient intelligence, collective intelligence and genetic intelligence. This classification categorizes the intelligence of robots based on the different aspects of awareness and the ability to act deliberately as a result of such awareness.

39 citations

Journal ArticleDOI
25 May 2022
TL;DR: This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022, and the competition set-up, datasets, proposed methods and their results.
Abstract: This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under-or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).

24 citations

Journal ArticleDOI
TL;DR: A decentralized MRTA approach considering the robots' residual expendable resources and their limited communication ranges that minimization of unnecessary task performance cost caused by resource shortage of robots during task execution and the use of an ad hoc network among the robots to allow more robots to participate in the task allocation process.
Abstract: The objective of multirobot task allocation (MRTA) is to assign tasks to robots to minimize the overall cost of task performance. This paper proposes a decentralized MRTA approach considering the robots' residual expendable resources and their limited communication ranges. The proposed approach consists of two algorithms, namely, resource-aware cost generation (RCG) and ad hoc network-based task allocation (ANTA). The RCG algorithm allows each robot to generate a credible cost of task performance considering its residual resources in task planning. The ANTA algorithm constructs the minimal spanning tree network among the robots and determines the robot with the lowest cost for the task through multihop communication in a decentralized manner. The advantages of the proposed approach are minimization of unnecessary task performance cost caused by resource shortage of robots during task execution and the use of an ad hoc network among the robots to allow more robots to participate in the task allocation process. The effectiveness of the proposed approach is demonstrated through computer simulations for multirobot foraging as a test problem.

22 citations

Journal ArticleDOI
TL;DR: The results show that the artificial creatures with various characteristics can be successfully created by the proposed DoC-MoT, and training the created artificial creatures to modify their characteristics was more efficient in the DoC -MoT than the probability-based mechanism of thought (P- MoT), both in terms of the number of parameters to be set and the amount of time consumed.
Abstract: To make artificial creatures deliberately interact with their environment like living creatures, a behavior selection method mimicking living creatures thought mechanism is needed. For this purpose, there has been research based on probabilistic knowledge links between input (assumed fact) and target (behavior) symbols for reasoning. However, real intelligent creatures including human beings select a behavior based on the multi-criteria decision making process using the degree of consideration (DoC) for input symbols, i.e. will and context symbols, in their memory. In this paper, the DoC-based mechanism of thought (DoC-MoT) is proposed and applied to the behavior selection of artificial creatures. The knowledge links between input and behavior symbols are represented by the partial evaluation values of behaviors over each input symbol, and the degrees of consideration for input symbols are represented by the fuzzy measures. The proposed method selects a behavior through global evaluation by the fuzzy integral, as a multicriteria decision making process, of knowledge link strengths with respect to the fuzzy measure values. The effectiveness of the proposed behavior selection method is demonstrated by experiments carried out with a synthetic character Rity in the 3D virtual environment. The results show that the artificial creatures with various characteristics can be successfully created by the proposed DoC-MoT. Moreover, training the created artificial creatures to modify their characteristics was more efficient in the DoC-MoT than the probability-based mechanism of thought (P-MoT), both in terms of the number of parameters to be set and the amount of time consumed.

17 citations


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Dissertation
01 Jan 1975

2,119 citations

01 Jan 2016
TL;DR: The the third wave is universally compatible with any devices to read and is available in the digital library an online access to it is set as public so you can get it instantly.
Abstract: Thank you for downloading the third wave. Maybe you have knowledge that, people have search hundreds times for their chosen readings like this the third wave, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some malicious bugs inside their laptop. the third wave is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the the third wave is universally compatible with any devices to read.

866 citations

Journal ArticleDOI
TL;DR: This paper follows on [1] to show how type-2 FLSs are starting to find their way into a variety of real world applications, promising a continuous growth both in number and variety of type-1 FLS applications in the next decade.
Abstract: Real world applications are characterized by high levels of linguistic and numerical uncertainties. Since the inception of Fuzzy Logic Systems (FLSs), they have been applied with great success to numerous real world applications. The vast majority of FLSs so far have been traditional type-1 FLSs. However, type-1 FLSs cannot fully handle the high levels of uncertainties available in the vast majority of real world applications. This is because type-1 FLSs employ crisp and precise type-1 fuzzy sets. A type-2 FLS can handle higher uncertainty levels to produce improved performance. This paper follows on [1] to show how type-2 FLSs are starting to find their way into a variety of real world applications, promising a continuous growth both in number and variety of type-2 FLS applications in the next decade.

137 citations

Journal ArticleDOI
09 Sep 2016-Sensors
TL;DR: This work uses BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot and adds two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty.
Abstract: A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm.

63 citations