The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
The emergence of grid and a new class of data-driven applications is making a new form of parallelism desirable, which we refer to as coarse-grained pipelined parallelism. This pa...
We present an algorithm for real-time level of detail reduction and display of high-complexity polygonal surface data. The algorithm uses a compact and efficient regular grid repr...
Peter Lindstrom, David Koller, William Ribarsky, L...
Distributed computing (DC) projects tackle large computational problems by exploiting the donated processing power of thousands of volunteered computers, connected through the Int...
Toni Giorgino, Matt J. Harvey, Gianni De Fabritiis
Abstract— Trajectory planning and optimization is a fundamental problem in articulated robotics. It is often viewed as a two phase problem of initial feasible path planning aroun...