Orientation-Aware Planning for Parallel Task Execution of Omni-Directional Mobile Robot

Collaborative Task Execution by a Human and an Autonomous Mobile Robot in a Teleoperated System

Integrated Computer-Aided Engineering ◽

10.3233/ica-1999-6405 ◽

1999 ◽

Vol 6 (4) ◽

pp. 319-330 ◽

Cited By ~ 2

Author(s):

Kuniaki Kawabata ◽

Tatsuya Ishikawa ◽

Teruo Fujii ◽

Hajime Asama ◽

Isao Endo

Keyword(s):

Mobile Robot ◽

Autonomous Mobile Robot ◽

Task Execution ◽

Collaborative Task

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Parallel Task Execution in a Decentralized System

IEEE Transactions on Computers ◽

10.1109/t-c.1972.223502 ◽

1972 ◽

Vol C-21 (12) ◽

pp. 1310-1322 ◽

Cited By ~ 15

Author(s):

M.J. Gonzalez ◽

C.V. Ramamoorthy

Keyword(s):

Task Execution ◽

Decentralized System ◽

Parallel Task

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Miniature Humanoid Upgrade for Material Handling Tasks in Humanoid Challenge

Volume 4: Dynamics, Vibration, and Control ◽

10.1115/imece2019-10193 ◽

2019 ◽

Author(s):

Kiwon Sohn ◽

Jeongkyu Lee ◽

Kevin Huang

Keyword(s):

Mobile Robot ◽

Material Handling ◽

Trinity College ◽

Software Components ◽

Task Execution ◽

Bipedal Robot ◽

Robot Platform

Abstract This paper presents the development of a miniature humanoid platform for various material-handling tasks. Since 2018, three universities in Connecticut (University of Hartford, University of Bridgeport and Trinity College) have made continuous efforts on building and organizing the annual robotics competition which is titled as Humanoid Challenge (HC). While most robotics competitions are concentrating on mobile robot and its navigation, HC focuses on the small-sized bipedal robot platform (miniature humanoid) and its task-execution in human-centered-environments. Inspired from DRC Trials 2013 and Finals 2015, the participants in the competition are asked to complete six different tasks in a mock-up of a disaster. To assist students and teams who are interested in participating in the competition, the authors in three universities share the progresses with both hardware and software components of each teams robot platform through this paper.

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Task Assignment and Scheduling for Mobile Robot Teams

Volume 5A: 42nd Mechanisms and Robotics Conference ◽

10.1115/detc2018-86007 ◽

2018 ◽

Cited By ~ 1

Author(s):

Shaurya Shriyam ◽

Satyandra K. Gupta

Keyword(s):

Mobile Robot ◽

Mobile Robots ◽

Completion Time ◽

Heuristic Algorithms ◽

Task Assignment ◽

Task Execution ◽

Computational Performance ◽

Robot Teams ◽

Or Task

Most complex missions comprise of spatially separated tasks which have to be finished using teams of mobile robots. The main challenges for planning such missions are forming effective coalitions among available robots and assigning them to tasks in such a way that the expected mission completion time is minimized. Our model allows task execution by a fraction of the assigned team even when the rest of the team has not yet arrived at the task location. We also allow tasks to be interrupted and robots of assigned teams to be rescheduled from an unfinished task to another task. We describe five different heuristic algorithms to compute schedules for all robots assigned to the mission. We compare them and analyze the computational performance of the best performing strategy. We also show how to handle uncertainty that may arise during traveling or task execution and then study the effect of varying uncertainty on the minimization of mission completion time.

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