4 accepted papers
We present a method for calculating the probability that a robot successfully performs a task described using Signal Temporal Logic (STL). We focus on cases where the failure probability is very small, hence a traditional Monte-Carlo method becomes inefficient due to the large number of samples requ…
We develop a method for synthesizing control policies for stochastic, linear, time-varying systems that must perform tasks specified in signal temporal logic. We build upon an efficient, sampling-based framework that computes the probability of the system satisfying its specification. By exploiting…
We introduce R3T, a reachability-based variant of the rapidly-exploring random tree (RRT) algorithm that is suitable for (optimal) kinodynamic planning in nonlinear and hybrid systems. We developed tools to approximate reachable sets using polytopes and perform sampling-based planning with them. Thi…
Piecewise affine (PWA) systems are widely used to model highly nonlinear behaviors such as contact dynamics in robot locomotion and manipulation. Existing control techniques for PWA systems have computational drawbacks, both in offline design and online implementation. In this paper, we introduce a…