Åke Wernersson

Mobile robot navigation using the range-weighted Hough transform

Accurate navigation of a mobile robot in cluttered rooms using a range-measuring laser as a sensor has been achieved. To extract the directions and distances to the walls of the room the range-weighted Hough transform is used. The following experimental results are emphasized: The robot extracts the walls of the surrounding room from the range measurements. The distances between parallel walls are estimated with a standard deviation smaller than 1 cm. It is possible to navigate the robot along any preselected trajectory in the room. One special case is navigation through an open door detected by the laser. The accuracy of the passage is 1 cm at a speed of 0.5 m/s. The trajectory is perpendicular to the wall within 0.5 degrees in angle. When navigating through corridors, the accuracy is better than 1 cm at 0.8 m/s-the maximum speed of the robot. Odometric data and laser measurements are combined using the extended Kalman filter. The size of the cluttered rectangular room and the position and orientation (pose) of the robot are estimated during motion. The extraction and the resulting navigation are very robust against both spurious measurements in the laser measurements and disturbing objects. >

Mobile robot localization: integrating measurements from a time-of-flight laser

This paper presents an algorithm for environment mapping by integrating scans from a time-of-flight laser and odometer readings from a mobile robot. The range weighted Hough transform (RWHT) is used as a robust method to extract lines from the range data. The resulting peaks in the RWHT are used as feature coordinates when these lines/walls are used as landmarks during navigation. The associations between observations over the time sequence are made in a systematic way using a decision directed classifier. Natural geometrical landmarks are described in the robot frame together with a covariance matrix representing the spatial uncertainty. The map is thus built up incrementally as the robot moves. If the map is given in advance, the robot can find its location and navigate relative to this a priori given map. Experimental results are presented for a mobile robot with a scanning range measuring laser having 2-cm resolution. The algorithm was also used for an autonomous plastering robot on a construction site. The sensor fusion algorithm makes few erroneous associations.

The Hough transform inside the feedback loop of a mobile robot

Accurate navigation of a mobile robot in cluttered rooms using a range measuring laser as a sensor is considered. The range weighted Hough transform (RWHT) is used to extract the directions and distances to the walls of the room. Using the extracted RWHT peaks in a feedback loop, the mobile robot is capable of a large variety of navigation tasks for navigating the robot through an open door detected by the laser, the accuracy during passage was found experimentally to be 1 cm at a speed of 0.5 m/s. For navigating through corridors, the accuracy was better than 1 cm at the maximum speed, 0.8 m/s, of the robot. Odometric data and laser measurements are combined using the extended Kalman filter. During motion, the size of the cluttered rectangular room is estimated as well as the position and the orientation (pose) of the robot. The navigation is very robust against both spurious laser measurements and disturbing objects.<<ETX>>

Navigating an articulated vehicle and reversing with a trailer

This paper describes two related tests; to navigate an articulated lawn mower and to reverse a mobile robot with a trailer. In both cases the vehicles are to follow a prespecified trajectory. The navigation principal is based on measured directions to several identical beacons, consisting of strips of reflective tapes. The angular sensor is a rotating laser for the illumination of the beacons and a highly sensitive electro-optical receiver for detecting the directions to the beacons. A Kalman filter is used to combine the measurements from the odometers with the detected angles to the known position of the beacons. To measure the angle between the robot and the trailer the same laser was used. This was done by placing two reflective beacons on the trailer. The repeatability was within 2 centimetre at low speed. The navigation of these two different types of vehicles turns out to be, essentially, the same problem. The sensitivities are different. Emphasis is on robust state estimation.<<ETX>>

On robot navigation using identical landmarks: integrating measurements from a time-of-flight laser

This paper presents an algorithm for fusing scans from a time-of-flight laser and odometer readings from the robot. The range weighted Hough transform is used as a robust method to extract lines from the range data. The resulting peaks are used as feature coordinates when these lines/walls are used as landmarks during navigation. The associations between observations over the time sequence are made in a systematic way using a decision directed classifier. Natural geometrical landmarks are described in the robot frame together with a covariance matrix representing the spatial uncertainty. The map is thus built incrementally as the robot moves. If the map is given in advance the robot can find its location and navigate relative to the map. Experimental results and simulations are presented for a mobile robot with a scanning range measuring laser with 2 cm resolution.<<ETX>>

Robust colour and range sensing for robotic applications using a stereoscopic light stripe scanner

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 the 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 validation/association 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 the operation in ambient light, the registered colour and range are captured in the same sensor. An experimental scanner demonstrates the effectiveness of the proposed techniques.

On covariances for fusing laser rangers and vision with sensors onboard a moving robot

Consider a robot to measure or operate on man made objects randomly located in the workspace. The optronic sensing onboard the robot are a scanning range measuring time-of-flight laser and a CCD camera. The goal of the paper is to give explicit covariance matrices for the extracted geometric primitives in the surrounding workspace. Emphasis is on correlation properties of the stochastic error models during motion. Topics studied include: (i) covariance of Radon/Hough peaks for plane surfaces; (ii) covariances for the intersection of two planes; (iii) equations for combining vision features, plane surfaces and range discontinuities; and (iv) explicit equations of how the covariance matrices are transformed during the robot motion. Typical applications are; models for verification and updating of CAD-models when navigating inside buildings and industrial plants, and accumulating sensor readings for a telecommanded robot.

A Construction Robot for Autonomous Plastering of Walls and Ceilings

The problem addressed is plastering of walls and ceilings during the construction of apartment and office buildings. The concrete walls are to be covered by a smooth layer of plaster, a few millimetres thick. The workspace is structured enough that map generation, navigation and motion planning can be performed autonomously. The robot must reliably avoid plastering windows and doors. Typical requirements on the navigation accuracy are standard deviations no greater than 1 cm. Two prototypes are described. For navigation the robot uses a range measuring sensors scanning in one (or two) planes. The observations are used to create, and continuously update, a mainly planar map with some vertical information i. e. door and window positions. The map generation and sensor fusion algorithms are based on a Bayesian association algorithm and an extended Kalman filter. Tests have been successfully performed at an actual construction site. The time used for plastering the walls and ceiling in a room is expected to be less than 50% of that required by manual work The amount of plaster used is also greatly reduced due to more even spraying. However the reasons for developing the robot is mainly ergonomic.

On Motion Estimation For A Mobile Robot Navigating In Natural Environment: Matching Laser Range Measurements Using The Distance Transform

The goal behind this paper is to find a generic method for controlling the motion of a robot relative to an object of an arbitrary shape. In this paper we study; - modelling laser range measurement ...

Remote CAN operations in MATLAB over the Internet

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.