Boris Kluge

Fast and robust tracking of multiple moving objects with a laser range finder

In this paper we focus on the task of tracking multiple moving objects in rapidly changing, dynamic environments. Objects are extracted from laser range finder images and correspondences between successive images are established by network optimization techniques. The approach is implemented on a robotic wheelchair, used in two applications and evaluated experimentally.

Motion coordination between a human and a mobile robot

In this paper we describe an approach to coordinating the motion of a human with a mobile robot moving in a populated, continuously changing, natural environment. The approach is based on a method for motion planning amongst moving obstacles known as the velocity obstacle approach. We extend this method by a method for tracking a virtual target which allows us to vary the robots heading and velocity with the locomotion of the accompanied person and the state of the surrounding environment. Our test application is a wheelchair accompanying a person through the concourse of a railway station.

Robot Position Estimation on a RFID-Tagged Smart Floor

We describe a navigation and position estimation system for mobile service robots which is based on RFID technology. This system avoids deficiencies of existing solutions and offers high flexibility and accuracy at moderate cost. The core idea of the system is to structure the work space by means of a Smart Floor in a manner which enables and supports reliable navigation and positioning with absolute accuracy over large distances. The “intelligence” of the floor is in a dense, area-wide network of thousands of RFID transponder, which are mounted underneath the regular floor covering and quasi serve as radio beacons. The system has been presented at CeBIT 2006 in Hannover by invitation of the German Ministry of Education and Research. InMach Intelligente Maschinen has further received the Walter Reis Innovation Award for Service Robotics for this innovative solution. It is important to note that although the primary focus of the work described in this paper is on the guidance of service robots in large-scale indoor environments, the Smart Floor described below provides the infrastructure for all kinds of location-based services which might be of relevance in a large facility. The economic value of these services may even exceed the economic value of automated cleaning.

Motion coordination between a human and a robotic wheelchair

We describe an approach to coordinating the motion of a human with a mobile robot moving in a populated, continuously changing, natural environment. Our test application is a wheelchair accompanying a person through the concourse of a railway station moving side by side with the person. In healthcare and rehabilitation scenarios this addresses a rather important issue. Pushing and maneuvering a carriage such as a wheelchair or a hospital bed, exposes the back of the pushing person to extreme significant often resulting in severe long-term back problems. Our approach is based on a method for motion planning amongst moving obstacles known as velocity obstacle approach. We extend this method by a method for tracking a virtual target which allows us to vary the robots heading and velocity with the locomotion of the accompanied person and the state of the surrounding environment.

Exploiting RFID Capabilities Onboard a Service Robot Platform

The potential of RFID (radio frequency identification) technology is analyzed in the context of service robots. Various concepts that differ by operation frequency (LF, HF, UHF) and, thus, by range are analyzed. Typically, the service robot application which is to be supported by RFID, preselects the frequency band by range requirements.

Motion coordination in dynamic environments: reaching a moving goal while avoiding moving obstacles

In this paper we describe the problem of coordinating the motion of a mobile robot with a moving guide in dynamic, continuously changing environments, and present an approach to this problem based on velocity obstacles. As a test application, the approach has been implemented on a robotic wheelchair, which is thus enabled to accompany a person through the concourse of a railway station or a pedestrian area.

People tracking using omnidirectional vision and range information

In this paper we present two approaches for tracking of people in dynamic environments with a moving sensor system. The trajectories of persons are used to extract simple motion patterns. Object detection and tracking is based on range and color information which is provided by a laser range finder and a omnidirectional color camera. Without any predefined person-model the system acquires an internal representation of the person at an initialization phase. This representation is tracked in real-time in dynamic environments. During the tracking procedure illumination conditions are continuously monitored. The tracking approaches were implemented on a robotic wheelchair and evaluated experimentally in different dynamic environments.

Navigation in Landmark Networks

Service robots for everyday use must maneuver accurately and repeatably throughout their work space. For large work spaces this, today still, requires some sort of devices like landmarks from which robot positions can be inferred. Here, trilateration is considered which means that robot positions are inferred from distances between landmarks and the robot. While robot localization calls for precision and, hence, for many landmarks, commercial issues call for few landmarks. The issue of their suitable placement prevails in both cases.

Services Robots Navigating on Smart Floors

We describe an approach to position estimation for mobile service robots and automatically guided vehicles which is based on RFID technology. The core idea of the approach is to structure the work space by means of a Smart Floor in a manner which enables and supports reliable navigation and positioning with absolute accuracy over large distances. The “intelligence” of the floor is in a dense, area-wide network of thousands of RFID transponder, which are mounted underneath the regular floor covering and quasi serve as radio beacons. The navigation system described in this paper, has been presented at CeBIT 2006 in Hannover by invitation of the German Ministry of Education and Research. InMach Intelligente Maschinen has further received the Walter Reis Innovation Award for Service Robotics for this innovative solution.

Statistical recognition of motion patterns

One key prerequisite for a machine to interact intelligently with people is its ability to recognize humans as interaction partners, and to understand their behaviors and the intentions and plans behind them. In this paper we are particularly interested in behaviors which are related to motion, e.g. intentionally moving towards a goal or obstructing somebodys path. More specifically, we address the problem of detecting and tracking people in natural dynamic environments in realtime, and extracting and classifying typical motion patterns. Robust detection and tracking of nonrigid objects in natural changing environments with a moving observer is a challenging problem. Although various sophisticated approaches have been presented, robustness with respect to changing light conditions, non-rigidness of the tracked objects, occlusion and motion of the observer is still a problem which needs for an effective solution. Recognizing and understanding the intention of motion would leverage applications in areas such as smart environments, human-machine interaction and video surveillance. We present an approach for tracking people by integrating range information and visual information, and using their complimentary strengths to overcome typical tracking problems. Individual motion trajectories are extracted from these fused sensor data and are condensed in compact statistical spatiotemporal models. These models serve as a basis for the extraction of typical motion patterns by unsupervised learning.