Dirk Wollherr | Technische Universität München (original) (raw)

Papers by Dirk Wollherr

IEEE Transactions on Vehicular Technology, Apr 1, 2016

Springer eBooks, 2009

ABSTRACT Ball dribbling is a central element of basketball. One main challenge for realizing bask... more ABSTRACT Ball dribbling is a central element of basketball. One main challenge for realizing basketball robots is to achieve the stability of the periodic dribbling task. We show that the dribbling problem is closely related to robot juggling problems that are well-studied. To this end, the paper introduces a hybrid (discretecontinuous) dynamical model for ball dribbling that provides the basis for the design of reference trajectories and controllers. Furthermore the paper discusses local stability and parameter sensitivity in particular in comparison to juggling. Theoretical results are experimentally validated for ball dribbling using an industrial robot. Force/torque-based tracking and vision-based tracking are compared. For both tracking approaches, dribbling for multiple cycles is achieved. The visionbased approach performs better as compared to the force/torque-based approach, in particular for imprecise estimates of the coefficient of restitution.

IEEE Transactions on Control Systems and Technology, Nov 1, 2020

During autonomous driving, in particular conditional or highly automated driving, a critical part... more During autonomous driving, in particular conditional or highly automated driving, a critical part of the system is the driver take over request. Little focus has been given to this important aspect in an automated driving journey. A driver take over request, or TOR, can happen for various reasons and under varying circumstances. Once a TOR occurs, as defined in conditional or highly automated driving, the driver has a finite amount of time in order to take over manual control of the vehicle before the automated driving system deactivates. This paper presents a detailed analysis of why a TOR can occur, how the automated driving system should react during the TOR phase and what should happen at the end of a TOR in order to realize a safe and comfortable TOR for the driver. Various driving strategies during a TOR are presented and evaluated for a single-lane highway scenario.

IEEE Transactions on Automation Science and Engineering, 2021

2015 IEEE Intelligent Vehicles Symposium (IV), 2015

2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2017

Humans are error-prone in the presence of multiple similar tasks. While Human-Robot Collaboration... more Humans are error-prone in the presence of multiple similar tasks. While Human-Robot Collaboration (HRC) brings the advantage of combining the superiority of both humans and robots in their respective talents, it also requires the robot to communicate the task goal clearly to the human collaborator. We formalize such problems in interactive assembly tasks with hidden goal Markov decision processes (HGMDPs) to enable the symbiosis of human intention recognition and robot intention expression. In order to avoid the prohibitive computational requirements, we provide a myopic heuristic along with a feature-based state abstraction method for assembly tasks to approximate the solution of the resulting HGMDP. A user study with human subjects in round-based LEGO assembly tasks shows that our algorithm improves HRC and helps the human collaborators when the task goal is unclear to them.

IEEE Transactions on Vehicular Technology, 2016

IEEE Transactions on Intelligent Transportation Systems, 2019

International Journal of Social Robotics, 2016

Next generation of industrial revolution will be featured with broad applications of intelligent ... more Next generation of industrial revolution will be featured with broad applications of intelligent technologies; among those popular ones are intelligent manufacturing and autonomous products like vehicles and robotic systems. In both cases, autonomous operations are at the center of the stage, in which appropriate sensing and perception play critical roles. Indeed, recent advances in sensing and perception technologies have produced exciting new ideas in facilitating autonomous manufacturing and/or robotic vehicular systems. These technologies will potentially evolve with more and more ‘smart functions’ and move manufacturing and robotic systems from single structured operation to sensing/perception-based self-governed yet collaborative multisystem operations. This Focused Section is dedicated to new progresses in modeling, design, control, communication, and implementation of sensing and perception systems for autonomous and/or networked robotics, and intends to provide the state-of...

International Journal of Intelligent Robotics and Applications, 2017

2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO), 2015

Within Human-Robot Collaboration (HRC) safety is one key-issue that has to be guaranteed at any t... more Within Human-Robot Collaboration (HRC) safety is one key-issue that has to be guaranteed at any time during joint collaboration. Collisions in a shared workspace of a Human-Robot-Team (HRT) must be prevented. In addition, the comfort of the collaboration behavior should be provided. Facing these challenges, a robot has to be able to detect critical states at an early stage on the one hand and should react to them within a very short time span on the other hand. In this paper a collision avoidance algorithm using compliance control that guarantees a fast reaction to dynamic obstacles, e.g. humans, without the need of high computational effort is outlined. To further improve the avoidance behavior of the robot, a human motion prediction algorithm based on the minimum-jerk model is integrated. In an experimental analysis of a case-study about collecting LEGO-bricks on a table with various subjects, the impact of the integration of human motion prediction on both the robot's reaction time and human's perception of the robot co-worker is studied. Finally, the comfort and acceptance of the robot colleague by the human collaborator is drawn out through an analysis of the subjective human feedback questionnaires.