Bilevel optimization is defined as a mathematical program, where an optimization problem
contains another optimization problem as a constraint. These problems have received …

In the last decade, the objectives outlined by the needs of personal robotics have led to the
rise of new biologically-inspired techniques for arm motion planning. This paper presents a …

Bilevel optimization problems are hierarchical optimization problems where the feasible
region of the so-called upper level problem is restricted by the graph of the solution set …

In this article, we study the problem of multiple stochastic agents interacting in a dynamic
game scenario with continuous state and action spaces. We define a new notion of …

In this study, we present a framework that infers human activities from observations using
semantic representations. The proposed framework can be utilized to address the difficult …

To enable safe and efficient human-robot collaboration in shared workspaces, it is important
for the robot to predict how a human will move when performing a task. While predicting …

Abstract Obstacle avoidance for Dynamic Movement Primitives (DMPs) is still a challenging
problem. In our previous work, we proposed a framework for obstacle avoidance based on …

Inverse optimal control (IOC) assumes that demonstrations are the solution to an optimal
control problem with unknown underlying costs, and extracts parameters of these underlying …

Predictive simulation based on dynamic optimization using musculoskeletal models is a
powerful approach for studying human gait. Predictive musculoskeletal simulation may be …

It is a common belief that service robots shall move in a human-like manner to enable
natural and convenient interaction with a human user or collaborator. In particular, this …