— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
This paper integrates research in robot programming and reasoning about action with research in model-based reasoning about physical systems to provide a capability for modeling an...
Abstract— We describe how a graph grammar program for robotic self-assembly, together with measurements of kinetic rate data yield a Markov Process model of the dynamics of progr...
Cyclic genetic algorithms can be used to generate single loop control programs for robots. While successful in generating controllers for individual leg movement, gait generation,...
Effective human/robot interfaces which mimic how humans interact with one another could ultimately lead to robots being accepted in a wider domain of applications. We present a fr...
Paul E. Rybski, Kevin Yoon, Jeremy Stolarz, Manuel...