A mobile robot needs to be aware of its environment to interact with it safely. We propose a
receding horizon control scheme for mobile manipulators that tracks task space reference …

This article presents the concept of model predictive interaction control (MPIC) as a generic,
flexible, and comprehensive approach for robotic manipulation tasks. MPIC is based on the …

Control tasks in various applications are posed as setpoint-stabilization problems, where a
constant reference has to be stabilized. For systems where changing references are given …

Robots are more and more often designed in order to perform tasks in synergy with human
operators. In this context, a current research focus for collaborative robotics lies in the design …

This paper presents a trajectory generation method for a nonlinear system under closed-
loop control (here a quadrotor drone) motivated by the Nonlinear Model Predictive Control …

Various cognitive systems have been designed to model the position and stiffness profiles of
human behavior and then to drive robots by mimicking the human's behavior to accomplish …

The development of modern sensitive lightweight robots allows the use of robot arms in
numerous new scenarios. Especially in applications where interaction between the robot …

The control of the interaction between the robot and environment, following a predefined
geometric surface path with high accuracy, is a fundamental problem for contact-rich tasks …

Many robotic tasks, such as human-robot interactions or the handling of fragile objects,
require tight control and limitation of appearing forces and moments alongside sensible …

In the literature about model predictive control (MPC), contact forces are planned rather than
controlled. In this paper, we propose a novel paradigm to incorporate effort measurements …