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This article presents a series of evolutionary robotics experiments that operationalize such concept, training miniature two-wheeled mobile robots to autonomously solve a temporal task.
The mobile robot application coordinates a set of mobile robots to detect chemical spills.
Simultaneous localization and mapping (SLAM) is the crucial prerequisite for mobile robots to accomplish autonomy.
In this subsection, we propose two range-only control schemes to drive wheeled mobile robots to rendezvous.
Different fields like factories, hospitals and houses require mobile robots to navigate autonomously and to perform tasks by themselves.
It is important for mobile robots to cope with map errors in order to execute tasks in a real environment.
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We address the problem of controlling a mobile robot to explore a partially known environment.
The Kalman filter (KF) has been improved for a mobile robot to human tracking.
In this strategy, the user first guides a mobile robot to a destination by remote control.
"That's very important for a mobile robot to have.
This paper presents a new image based visual tracking scheme for a mobile robot to trace a moving target using a single camera mounted on the mobile robot.
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