It showed great potential to apply this algorithm in other related fields including mobile robots exploration.
For mobile robots, exploration in an unknown environment is always a fundamental problem in various areas, such as rescue and mining.
One prominent example involves semiautonomous mobile robots for exploration of the Martian surface.
We propose a new concept for life-long mobile robot spatio-temporal exploration that aims at building, updating and maintaining the environment model during the long-term deployment.
Neural controllers producing mobile robot maze searching and exploration behaviors using binary tactile sensors as inputs were evolved in a simulated environment and subsequently transferred to and tested on real robots in a physical environment.
In particular, we identify many attempts to use contextual knowledge in several basic functionalities of a mobile robot such as: behavior, navigation, exploration, localization, mapping and perception.
This paper describes the design of a mobile robot for outdoor surveillance and exploration tasks following the design methodology for mechatronic systems.
In this paper, we present an autonomous virtual mobile robot (AVMR) for three-dimensional (3D) exploration of unknown tubular-like structures in 3D images.
Many multiple robots and cooperation researches were focusing on the mobile robot application, e.g., robot soccer, task allocation, area exploration, robot formation, and swarm robotics [4-7].
Gaining high mobility on versatile terrains is a crucial target for designing a mobile robot toward tasks such as search and rescue, scientific exploration, and environment monitoring.
