We address the risk bounded trajectory optimization problem of stochastic nonlinear robotic
systems. More precisely, we consider the motion planning problem in which the robot has …

Fault-tolerant coverage control involves determining a trajectory that enables an
autonomous agent to cover specific points of interest, even in the presence of actuation …

While many techniques have been developed for chance constrained stochastic optimal
control with Gaussian disturbance processes, far less is known about computationally …

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We develop refined probability bounds for bank insolvency risk measures based on the Z-
score, analogous to those given by Cantelli's inequality under the additional assumption of …

This work proposes an open-loop methodology to solve chance constrained stochastic
optimal control problems for linear systems with a stochastic control matrix. We consider a …

We propose an open loop control scheme for linear systems with time-varying random
elements in the plant's state matrix. This paper focuses on joint chance constraints for …

We propose an open loop methodology based on sample statistics to solve chance
constrained stochastic optimal control problems with probabilistic safety guarantees for …

Stochastic disturbances arise in a variety of engineering applications. For tractability,
Gaussian disturbances are often assumed. However, this may not always be valid, such as …

This thesis considers risk aware planning and probabilistic prediction for autonomous
systems under uncertain environments. Motion planning under uncertainty looks for …