Customising navigational control for autonomous robotic mapping platforms is still a challenging task. Control software must simultaneously maximise the area explored whilst maintaining safety and working within the constraints of the platform. Scoring functions to assess navigational options are typically written by hand and manually refined. As navigational tasks become more complex this manual approach is unlikely to yield the best results. In this paper we explore the automatic derivation of a scoring function for a ground based exploration platform. We show that it is possible to derive the entire structure of a scoring function and that allowing structure to evolve yields significant performance advantages over the evolution of embedd...
Abstract: This paper presents a method for optimizing reference tracks used as input by an autonomou...
Abstract — The problem of Adaptation from Participation (AfP) aims to improve the efficiency of a hu...
This paper explores the application of genetic algorithms to the learning of local robot navigation ...
Autonomous robotic exploration is the task of building models of an environment. This task requires ...
An autonomous mobile robot requires a robust onboard controller that makes intelligent responses in ...
An approach is presented for the evolutionary development of supervised autonomous navigation capabi...
Area exploration and mapping with teams of robots is a challenging application. As the complexity of...
This paper presents an autonomous evolutionary system applied to control a mobile robot in unknown e...
An autonomous mobile robot requires an onboard controller that allows it to perform its tasks for lo...
In many robotic exploration missions, robots have to learn specific poli-cies that allow them to: (i...
Abstract—We present a coactive learning algorithm to solve the problem of learning a human expert’s ...
A novel solution to the problem of exploration and mapping of an unknown environment by an autonomou...
This paper deals with the problem of autonomous navigation of a mobile robot in an unknown 2D enviro...
Many applications of autonomous robots depend on the robot being able to navigate in real world envi...
Navigation in large-scale environments is composed of dierent local tasks. To achieve smooth switchi...
Abstract: This paper presents a method for optimizing reference tracks used as input by an autonomou...
Abstract — The problem of Adaptation from Participation (AfP) aims to improve the efficiency of a hu...
This paper explores the application of genetic algorithms to the learning of local robot navigation ...
Autonomous robotic exploration is the task of building models of an environment. This task requires ...
An autonomous mobile robot requires a robust onboard controller that makes intelligent responses in ...
An approach is presented for the evolutionary development of supervised autonomous navigation capabi...
Area exploration and mapping with teams of robots is a challenging application. As the complexity of...
This paper presents an autonomous evolutionary system applied to control a mobile robot in unknown e...
An autonomous mobile robot requires an onboard controller that allows it to perform its tasks for lo...
In many robotic exploration missions, robots have to learn specific poli-cies that allow them to: (i...
Abstract—We present a coactive learning algorithm to solve the problem of learning a human expert’s ...
A novel solution to the problem of exploration and mapping of an unknown environment by an autonomou...
This paper deals with the problem of autonomous navigation of a mobile robot in an unknown 2D enviro...
Many applications of autonomous robots depend on the robot being able to navigate in real world envi...
Navigation in large-scale environments is composed of dierent local tasks. To achieve smooth switchi...
Abstract: This paper presents a method for optimizing reference tracks used as input by an autonomou...
Abstract — The problem of Adaptation from Participation (AfP) aims to improve the efficiency of a hu...
This paper explores the application of genetic algorithms to the learning of local robot navigation ...