2 citations · 2 across the 2 of their papers we have counts for
4 papers
Incremental Sampling-based Motion Planners Using Policy Iteration Methods
Oktay Arslan, Panagiotis Tsiotras
Recent progress in randomized motion planners has led to the development of a new class of sampling-based algorithms that provide asymptotic optimality guarantees, notably the RRT*…
Sampling-based Algorithms for Optimal Motion Planning Using Closed-loop Prediction
Oktay Arslan, Karl Berntorp, Panagiotis Tsiotras
Motion planning under differential constraints, kinodynamic motion planning, is one of the canonical problems in robotics. Currently, state-of-the-art methods evolve around kinodyn…
Information-Theoretic Stochastic Optimal Control via Incremental Sampling-based Algorithms
Oktay Arslan, Evangelos Theodorou, Panagiotis Tsiotras
This paper considers optimal control of dynamical systems which are represented by nonlinear stochastic differential equations. It is well-known that the optimal control policy for…
The Role of Vertex Consistency in Sampling-based Algorithms for Optimal Motion Planning
Oktay Arslan, Panagiotis Tsiotras
Motion planning problems have been studied by both the robotics and the controls research communities for a long time, and many algorithms have been developed for their solution. A…