From Human to Pushing Leader Robot: Leading a Decentralized Multirobot System for Object Handling

Wang, Z.-D.; Hirata, Yasuhisa; Takano, Y.; Kosuge, Kazuhiro

doi:10.1109/robio.2004.1521819

Cited by 6 publications

References 31 publications

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Using Google Glass in Human–Robot Swarm Interaction

Kapellmann-Zafra

Chen

Groß

2016

Towards Autonomous Robotic Systems

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Abstract. We study how a human operator can guide a swarm of robots when transporting a large object through an environment with obstacles. The operator controls a leader robot that influences the other robots of the swarm. Follower robots push the object only if they have no line of sight of the leader. The leader represents a way point that the object should reach. By changing its position over time, the operator effectively guides the transporting robots towards the final destination. The operator uses the Google Glass device to interact with the swarm. Communication can be achieved via either touch or voice commands and the support of a graphical user interface. Experimental results with 20 physical e-puck robots show that the human-robot interaction allows the swarm to transport the object through a complex environment.

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Using Google Glass in Human–Robot Swarm Interaction

Kapellmann-Zafra

Chen

Groß

2016

Towards Autonomous Robotic Systems

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Object transportation task by a human and a mobile robot

Pereira

Ferreira

et al. 2010

2010 IEEE International Conference on Industrial Technology

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This paper addresses the human-robot cooperation problem on object transportation tasks, particularly when a human grasps one side of the object while the other extremity is carried by the robot. The robot is equipped with a pair of infrared sensors used to obtain the load's status and apply it as a feedback to accomplish a specific task. A nonlinear controller is proposed to allow the robot to perform coordinated movements and thus help a human to carry an object from an initial position to a final goal with a defined position and orientation. The controller is proved to be asymptotically stable at the equilibrium point, which guarantees the accomplishment of the task. In contrast to other methods, the approach presented in this paper does not use either force or visual information to estimate the status of the robot and the object. In order to validate the proposed method some experiments are shown.

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