René van de Molengraft

Cooperative adaptive cruise control, design and experiments

The design of a CACC system and corresponding experiments are presented. The design targets string stable system behavior, which is assessed using a frequency-domain-based approach. Following this approach, it is shown that the available wireless information enables small inter-vehicle distances, while maintaining string stable behavior. The theoretical results are validated by experiments with two CACC-equipped vehicles. Measurement results showing string stable as well as string unstable behavior are discussed.

RoboEarth: connecting robots worldwide

In this paper, we present the core concept and the benefits of an approach called RoboEarth which will be highly beneficial for future robotic applications in science and industry. RoboEarth is a world-wide platform which robots can use to exchange position and map information as well as task-related, hardware-independent action recipes. This will enable manufacturers worldwide to break down their costs and efforts for reproducing software algorithms for robot behavior over and over again. The RoboEarth framework can store all relevant data from algorithms to complex behavior descriptions what allows robots to act autonomously in an unknown, unspecified environment. Especially in the field of interaction with humans RoboEarth can bring forward the behavior of robots and simplify the software design for developers in that field.

Iterative learning control of industrial motion systems

Abstract Repetitive and iterative learning control are control strategies for systems that perform repetitive tasks or on which periodic disturbances act. In the field of motion systems this occurs if disturbances are position dependent or if dynamics are excited in a similar way during each point to point motion. For this class of systems design procedures for feedback controllers are recapitulated and feedforward strategies are explained. Iterative learning control in particular is a powerful concept, and design rules can be used to reduce the error far above the feedback bandwidth for repeatedly operated machines. Experiments illustrate the value of these design rules.

Realtime motion path generation using subtargets in a rapidly changing environment

In this work an algorithm is proposed for path planning in a rapidly changing environment. The algorithm is computationally cheap and generates a sub-optimal smooth path with bounds on the allowed velocity, acceleration, and jerk. The algorithm is designed for holonomic omniwheel platforms. It outperforms potential field algorithms regarding both convergence and optimality. Furthermore, it is able to adapt fast in a rapidly changing environment due to the low computational cost in the order of ms for a single update, in contrast with computationally more expensive methods such as wavefront algorithms and global optimization methods, where the computational cost is mostly on the order of seconds. The algorithm will be tested via simulations and experiments.

Analytical and Experimental Modelling for Gain-Scheduling of a Double Scara Robot

A method and system for operating a questionnaire. One embodiment of the method comprises the steps of providing a plurality of questions, associating at least one condition with each of at least some of the questions, and storing each of the questions in an associated computer file. For each of said some of the questions, the at least one condition associated with the question is stored in the same computer file in which the question is stored. In accordance with this method, satisfied conditions are identified, the stored conditions are parsed and questions whose associated conditions are all satisfied, are identified, and the identified questions are presented to a respondent.

Learning intentions for improved human motion prediction

For many tasks, robots need to operate in human populated environments. Human motion prediction therefore is gaining importance. The concept of social forces defines virtual repelling and attracting forces from and to obstacles and points of interest. These social forces can then be used to model typical human movements given an environment and a persons intention. This work shows how such models can exploit typical motion patterns summarized by growing hidden Markov models (GHMMs) that can be learned from data online and without human intervention. An extensive series of experiments shows that exploiting the intended position estimated using a GHMM within a social forces based motion model yields a significant performance gain in comparison with the standard constant velocity-based models.

Creating and using RoboEarth object models

This paper presented an approach to create 3D object models for robotic and vision applications in a fast and inexpensive way compared to established approaches. By using the RoboEarth system for storing the created object models users have world-wide access to the data and can immediately reuse a model as soon as it was created and uploaded. The approach shows general applicability for different kinds of cameras. In this work this was shown by two example implementations for the recognition process of objects. The quality of the recognition can be verified in the video. Combined with the knowledge saved in the RoboEarth database the objects can also be properly classified.

Nonlinear control of a linear motion system

A lever action firearm having a receiver, a hammer, a lever pivotal about a fixed point, a bolt and a link which link is pivotal on both the bolt and the lever. The pivotal lever includes first surface means to engage second surface means on the hammer to cause the hammer to be cammed back during unloading. The lever, link and bolt are configured such that when they are in the fire position and are subjected to forces of firing they function as a joint lock to prevent unloading of the bolt and lever. Locking surfaces on the receiver and bolt strengthen the joint lock at the moment of firing.

Robust High Performance Bilateral Teleoperation Under Bounded Time-Varying Dynamics

The control design for bilateral teleoperation systems represents a challenge in finding the proper balance in the inherent tradeoff between transparency and stability. To address this problem, we propose a methodology in which we develop a parametric model of the teleoperation system. Subsequently, we exploit robust control techniques based on linear matrix inequalities to design controllers that aim to achieve a predefined performance, and are robust to bounded but arbitrarily fast-time-varying parametric uncertainties. We present analysis, simulation, and experimental results of the designed controller, thus showing that the assumptions made during modeling are appropriate and the effectiveness of the method to tradeoff perfect transparency and stability.

RoboCup MSL : history, accomplishments, current status and challenges ahead

The RoboCup Middle-Size League (MSL) is one of the founding leagues of the annual RoboCup competition. Ever since its birth it has been a league where development of hard- and software happens simultaneously in a real-world decentralized multi-robot soccer setting. Over the years the MSL achieved scientific results in robust design of mechatronic systems, sensor-fusion, tracking, world modelling and distributed multi-agent coordination. Because of recent rule changes which actively stimulate passing, matches in RoboCup MSL have become increasingly appealing to a general audience. Approximately five thousand spectators were present during last years final match. In this paper we present our plan to build on this momentum to further boost scientific progress and to attract new teams to the league. We also give a historical overview and discuss the current state of the MSL competition in terms of strengths, weaknesses, opportunities and threats.