Steen Kristensen

Active global localization for a mobile robot using multiple hypothesis tracking

We present a probabilistic approach for mobile robot localization using an incomplete topological world model. The method, called the multi-hypothesis localization (MHL), uses multi-hypothesis Kalman filter based pose tracking combined with a probabilistic formulation of hypothesis correctness to generate and track Gaussian pose hypotheses online. Apart from a lower computational complexity, this approach has the advantage over traditional grid based methods that incomplete and topological world model information can be utilized. Furthermore, the method generates movement commands for the platform to enhance the gathering of information for the pose estimation process. Extensive experiments are presented from two different environments, a typical office environment and an old hospital building.

Toward interactive learning for manufacturing assistants

The aim of the research presented in this paper is to develop a robot which can easily be instructed how to either perform tasks autonomously or in cooperation with humans. We describe the prototype of our Manufacturing Assistant and the methods developed for teaching new tasks and environments. The functionality has been demonstrated in a number of factory settings. In this paper, some application examples of our methods are presented.

Bin-picking with a solid state range camera

Abstract In this paper we present new work done on the bin-picking problem. The work was triggered by the advent of a new solid state range camera which enables the economic and robust use of range imagery in industrial robotic automation tasks. The application presented is that of pick-and-place of randomly oriented but known polyhedral objects in an industrial robotic work cell. The algorithms for segmentation, pose estimation, and grasp point determination are presented along with practical results from a real industrial grade work cell.

The Manufacturing Assistant: safe, interactive teaching of operation sequences

In this paper we describe our Manufacturing Assistant, a mobile manipulator for future flexible manufacturing, and its capabilities for interactively learning new operation sequences. As an example we present a method for interactively teaching an order-picking task. The task is taught using a laser pointer and a hand-held computer. Furthermore, the system interacts with the user using speech output. The system was successfully demonstrated on the Hannover Industrial Fair 2002.

An experimental comparison of localisation methods, the MHL sessions

In this paper we compare multi hypothesis localisation (MHL)-which is a mobile robot localisation method based on multi hypothesis tracking - with six other methods reported in the literature. The comparison is performed using a standard set of test data and corresponding evaluation tools, thus facilitating a direct comparison of the obtained results. The experiments show that MHL compares favourably to all other methods in terms of recovering when the robot has been kidnapped. When using a validation gate for filtering out noisy measurements, MHL and the standard extended Kalman filter both perform as well as all other reported methods in terms of accuracy while being faster to compute.

Human-friendly interaction for learning and cooperation

In this paper, research towards a learning, cooperative robotic assistance is presented. The aim of this research is to develop a robot which can easily be instructed how to either perform task autonomously or in cooperation with humans. We describe the underlying representations and methods developed for teaching new tasks and environments. The functionality has been demonstrated in a number of factory and office settings. In this paper, an example from a service scenario in an office environment is presented.

Towards interactive learning for manufacturing assistants

In this paper, research towards interactive learning for manufacturing Assistants is presented. The aim of this research is to develop a robot which can easily be instructed as how to either perform tasks autonomously or in co-operation with humans. We describe the prototype of our manufacturing assistant and the methods developed for teaching new tasks and environments. The functionality has been demonstrated in a number of factory settings. In this paper, some application examples of our methods are presented.

Dynamic work space surveillance for mobile robot assistants

Intelligent mobile robot assistants are important components for increasing flexibility in future production processes. These robot assistants must be able to work autonomously but must also have the capability to interactively learn from and cooperate with the human worker in a common (shared) work space. They may under no circumstances be a subject of danger to the human worker wherefore new methods for work space surveillance are called for. In this paper we present the current state of the DaimlerChrysler manufacturing Assistant and the safety concept for the dynamic sensor-based surveillance of its work space.

Tactile Man-Robot Interaction for an Industrial Service Robot

In this paper, research towards a cooperative robotic assistant for manufacturing environments is presented. The aim of this research is to develop a robotic assistant which can easily be instructed how to either perform tasks autonomously or in cooperation with humans. Focus of this paper is on the tactile interaction between man and robot which is used for teaching as well as for direct cooperation in tasks jointly performed by worker and robot.

Computation of optimal and collisionfree movements for mobile robots

In this paper we present a method for calculating optimal, collisionfree movements for nonholonomic mobile robots. This is formulated as a nonlinear optimal control problem and solved using advanced numerical methods. The concept of artifical potential fields is used for accounting for the obstacles in the environment. Apart from taking advantage of the large body of knowledge from the numerical methods community this has the virtue of facilitating a simple and general problem description. Experiments show that using this method, complex movements can be calculated in a timely fashion.