A Vision-Based Trajectory Controller for Autonomous Cleaning Robots

Gerstmayr, Lorenz; Röben, Frank; Krzykawski, Martin; Kreft, Sven; Venjakob, D.; Möller, Ralf

doi:10.1007/978-3-642-10284-4_9

Cited by 6 publications

(12 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, in some applications, e.g. the cleaning applications we have in mind (Gerstmayr et al 2009), snapshot and current view are sometimes collected significantly far apart in time and after long spatial distances have been covered, such that a tracking of features is not feasible. We will therefore in the following focus on the more complex but more generally applicable local visual homing methods.…”

Section: Visual Navigation Methodsmentioning

confidence: 99%

“…the incorporation of distance and angular information into topological maps, see e.g. Hübner and Mallot 2007) or triangulation (such an application of one of the methods introduced in this paper for cleaning robot control is described by Gerstmayr et al 2009). In these cases, only the bearing of a snapshot location is computed but this location is not approached.…”

Section: Introductionmentioning

confidence: 99%

“…We assume that problems of the warping method (like mismatches or violations of the equal-distance assumption) up to a certain point only lead to small deviations of the home vector from its correct direction, but beyond this point cause warping to produce more or less randomly distributed home vectors. The precision of the home vectors as expressed by the spread is crucial for applications where the home vectors are used for triangulating positions rather than for homing (Gerstmayr et al 2009). An expected direct relation between the error and the size of the catchment area could not be found for our data (see Sect.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Three 2D-warping schemes for visual robot navigation

2010

Self Cite

View full text Add to dashboard Cite

Warping (Franz et al., Biological Cybernetics 79(3), 191-202, 1998b) and 2D-warping (Möller, Robotics and Autonomous Systems 57(1), [87][88][89][90][91][92][93][94][95][96][97][98][99][100][101] 2009) are effective visual homing methods which can be applied for navigation in topological maps. This paper presents several improvements of 2D-warping and introduces two novel "free" warping methods in the same framework. The free warping methods partially lift the assumption of the original warping method that all landmarks have the same distance from the goal location. Experiments on image databases confirm the effect of the improvements of 2D-warping and show that the two free warping methods produce more precise home vectors and approximately the same proportion of erroneous home vectors. In addition, two novel and easier-to-interpret performance measures for the angular error are introduced.

show abstract

Section: Visual Navigation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Three 2D-warping schemes for visual robot navigation

2010

Self Cite

View full text Add to dashboard Cite

show abstract

“…These robots are a popular application of mobile robotics, being extensively sold on the commercial market. Our research group also has a long-standing interest in this application [31][32][33]. Specifically, we have previously developed a prototype for an autonomous floor-cleaning robot, shown in Figure 2.…”

Section: Contributions Of This Studymentioning

confidence: 99%

“…Table 2 lists the specific values tested during our experiments. For the image-space method, we determine the factor a from Equation (30) using cross-validation: Given a location L, the set T L contains all tilted images not captured at L. Next, we compute the factor a L by applying Equation (31) to the m = (43 − 1) × 6 images in T L . For images taken at location L, we then calculate the tilt angle α by using Equation (30) with a = a L .…”

Section: Experiments Designmentioning

confidence: 99%

Visual Tilt Estimation for Planar-Motion Methods in Indoor Mobile Robots

Fleer

2017

Robotics

View full text Add to dashboard Cite

Visual methods have many applications in mobile robotics problems, such as localization, navigation, and mapping. Some methods require that the robot moves in a plane without tilting. This planar-motion assumption simplifies the problem, and can lead to improved results. However, tilting the robot violates this assumption, and may cause planar-motion methods to fail. Such a tilt should therefore be corrected. In this work, we estimate a robot's tilt relative to a ground plane from individual panoramic images. This estimate is based on the vanishing point of vertical elements, which commonly occur in indoor environments. We test the quality of two methods on images from several environments: An image-space method exploits several approximations to detect the vanishing point in a panoramic fisheye image. The vector-consensus method uses a calibrated camera model to solve the tilt-estimation problem in 3D space. In addition, we measure the time required on desktop and embedded systems. We previously studied visual pose-estimation for a domestic robot, including the effect of tilts. We use these earlier results to establish meaningful standards for the estimation error and time. Overall, we find the methods to be accurate and fast enough for real-time use on embedded systems. However, the tilt-estimation error increases markedly in environments containing relatively few vertical edges.

show abstract