Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
This paper focuses on the assignment of discrete points among K robots and determining the order in which the points should be processed by the robots, in the presence of geometric...
Nilanjan Chakraborty, Srinivas Akella, John T. Wen
We propose a non-persistent indoor localization system using a self-organizing reference grid of autonomous robot systems. The key idea is to continuously maintain accurate relati...
In this paper we address the challenge of realizing full-body behaviors in scalable modular robots. We present an experimental study of a biologically inspired approach to organize...
David Johan Christensen, Jason Campbell, Kasper St...
In this paper, we address the problem of lifelong map learning in static environments with mobile robots using the graph-based formulation of the simultaneous localization and mapp...
Henrik Kretzschmar, Giorgio Grisetti, Cyrill Stach...
This paper presents a story about consciousness and future of reception robots. A prototype version of reception robot is developed at university of Essex for university open days ...
We propose a constructive control design for stabilization of non-periodic trajectories of underactuated robots. An important example of such a system is an underactuated “dynam...
Ian R. Manchester, Uwe Mettin, Fumiya Iida, Russ T...
We consider the problem of controlling multiple robots manipulating and transporting a payload in three dimensions via cables. Individual robot control laws and motion plans enable...
Jonathan Fink, Nathan Michael, Soonkyum Kim, Vijay...
—We present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The changing environment is modeled as a field which grows in location...
This paper presents a SLAM algorithm for a team of mobile robots exploring an indoor environment, described by adopting the M-Space representation of linear features. Each robot so...
Daniele Benedettelli, Andrea Garulli, Antonio Gian...