This paper presents statistics on registrations from laser range finders in snowfall. The sensors are standard laser range finders in robotics, the LMS200 and the URG-04LX. Three different working cases were identified for the pulsed laser range finder. 1) Normal operation with background objects present within the range of the sensor. 2) Close range objects where ranges to objects are shorter than the pulse length. 3) Free-space in the background. The findings are summarized as: Two laser range finders have been used, one that sends out a pulsed wide beam and one with a modulated narrow laser beam. The narrow beam laser has better penetration between the snowflakes. Median filtering shows a substantial reduction in snowflake detects. The gamma distribution describes fairly well the range distribution of detected snowflakes. In an intense snowfall where about 24% of the ranges detected snowflakes. A time-polar median filter showed good results in suppressing snowflakes in range data

This paper is towards reducing the clutter from snowflakes for outdoor robots. There are three basic cases: 1. Normal operation of the laser with objects within range for detection. 2. Close range with objects close to the laser i.e. shorter than the pulse length. 3. Free space as background i.e. all detects are false. The findings are summarized as: The two lasers used were a pulsed wide beam laser and a modulated narrow beam laser. The narrow beam laser has much better penetration between the snowflakes. We did not use snow and rain threshold setting for the wide beam laser. Median filtering shows a substantial reduction in snowflake detects. The gamma distribution describes fairly well the distribution of detected snowflakes.

This paper describes the autonomous car that is being built for the RobotDay competition, arranged by SICK GmbH. The basic rule is to let an autonomous vehicle drive a track as fast as possible, based on any sensor technology. For this race SICK donated one S300 professional proximity sensor to each team. Our vehicle will use the circle sector expansion (CSE) method to avoid obstacles and to find its way along the track. We show initial results where the CSE method was used to guide the vehicle through a test track defined by cones and other objects.

We introduce snowBOTs as a generic name for robots working in snow. This paper is a study on using scan ning range measuring lasers towards an autonomous snow cleaning robot, working in an environment consisting al most entirely of snow and ice. The problem addressed here is using lasers for detecting the edges generated by "the snow meeting the road". First the laser data were filtered using his togram/median to discriminate against falling snowflakes and small objects. Then the road surface was extracted us ing the range weighted Hough/Radon transform. Finally the left and right edges of the road was detected by thresh olding. Tests have been made with a laser on top of a car driven in an automobile test range just south of the Arctic Circle. Moreover, in the campus area, the algorithms were tested in closed loop with the laser on board a robotized wheelchair.

If a wheelchair for disabled is used for semi-autonomous navigation indoors it must be able to navigate through doors. A door and doorway can be parameterized with five parameters. A divide and conquer implementation of the Hough transform is used to segment outlines from range scans. The client software remote controls the wheelchair from the MATLAB environment. The software consists of several Java threads that run concurrently. Sensor data are polled by threads and put into databases to reduce the network lag. The databases are used by a controller and a Kalman filter. Since most of the implementation is coded in Java it is possible to run it as a stand alone program on a computer that has Java installed. From 10 runs the trajectory offset was calculated to 0.9 cm with a standard deviation of 1.4 cm. The standard deviation of the heading was 2.2 degrees. This performance is essentially independent of the initial starting pose

This paper describes the implementation of a CAN server that acts as a CAN tool to a client. It can be used to monitor, observe and send messages to a distant CAN network over IEEE802.11b (Wave-LAN). The CAN server is controlled by one or several clients that can connect to it by TCP/IP. It is possible to send and receive CAN messages over Internet from a MATLAB environment since the client software is written in Java. The CAN server collects CAN messages and stores them into a ring buffer. The messages in the ring buffer are classified by their identifier and stored into a database. The CAN tool has been used in a demonstrative application example that consist of a remotely controlled wheelchair. In the example the wheelchair was programmed to run in a square. The positions obtained by odometric CAN messages are compared with the position from the navigation system onboard the wheelchair.

The problem addressed is control of robots and/or sensing, in workspaces at remote locations. Topics taken up in this plenary talk includes laser sensing, scene interpretation, telecommands for local autonomy, research issues especially for multirobot systems. Applications includes aerospace testing in north Sweden.

Telecommands are studied for high level control of robots over a communication channel with a non-neglectable time delay, time jitters and variable bandwidth. The sensors onboard the robot are a time-of-flight range measuring laser and a video camera. A few images are used by the operator for interpreting the scene. From the interpretations of the workspace around the robot, the operator specifies interactively the sequence of individual operations during a composite task. Each telecommand is then executed autonomously by closing the feedback loop between the robot and the objects in the surrounding workspace.

This paper presents an integrated, low-level approach to removing sensor noise, cross talk, spurious specular reflections, and solving the association problem in a light stripe scanner. Most single-camera scanners rely on the laser brightness exceeding that of the entire image. Our system uses two cameras to measure the stripe and combines knowledge of the light plane orientation to produce useful validation properties. The key result is the development of a condition relating image plane measurements and camera intrinsic parameters, which allows validationlassociation to be performed independently of 3D reconstruction. The same equations are used to improve ranging accuracy compared to single-camera systems. We also show how the system may be self-calibrated using measurements of an arbitrary nonplanar target. As validation allows operation in ambient light, registered colour and range are captured in the same sensor. An experimental scanner demonstrates the effectiveness of the proposed techniques.