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This paper presents a unified distributed optimal control approach for multiple autonomous robots' cooperative tracking as well as obstacle avoidance.
This paper presents a new architecture for coordinating multiple autonomous robots in the execution of cooperative tasks.
In this paper, we consider an extension of the Simultaneous Multiple STC (S-MSTC) algorithm, which we proposed in our previous work on multiple autonomous robots used in exploration and coverage in an unknown terrain.
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This paper proposes a new communication and control architecture which improves the capability and the flexibility of multiple autonomous robot systems in performing a complicated task and coping with unpredictable situations.
Coordination strategies and algorithms for a system with multiple autonomous mobile robots often require a robot to know the relative position of other robots in its vicinity (Beni and Wang, 1991; Wang, 1993; Wang and Premvuti, 1994).
It is based upon a media access protocol, CSMA/CD-W (Carrier Sense Multiple Access with Collision Detection for Wireless), which supports wireless inter-robot communication among multiple autonomous mobile robots without using any centralized mechanism.
This paper proposes a new strategy of evolution and adaptation of a population of multiple autonomous mobile robots to make multi-robot systems more flexible and robust against unpredictable environmental conditions and human operator's capricious commands, and to overcome the limitation of biologically inspired techniques which need a certain degree of redundancy and diversity.
In the proposed system, multiple autonomous monitoring robots are deployed around a remote-controlled working robot, and observe the objects that are highly related to the remote-controlled robot.
This paper describes the realization of a space-division optical communication system specifically designed to perform local inter-robot communication in fully distributed multiple autonomous mobile robot systems.
It's a networked technology that lets one user simultaneously control and coordinate multiple semi-autonomous robots via a touchscreen Tablet PC.
Autonomous robots interacting with humans in an evolving environment need the ability to acquire knowledge from their multiple perceptual channels in an unsupervised way.
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