— Computationally efficient motion planning must avoid exhaustive exploration of configuration space. We argue that this can be accomplished most effectively by carefully balan...
— 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, ...
— Randomly expanding trees are very effective in exploring high-dimensional spaces. Consequently, they are a powerful algorithmic approach to sampling-based single-query motion p...
In a number of industrial, space, or mobile systems applications, reaction forces and moments transmitted by a manipulator to its base are undesirable. Based on force and moment t...
Abstract-- Motion planning of deformable objects is challenging due to the high degrees-of-freedom inherent in deformation as well as the computational cost of producing physically...