Global Localization Based on 3D Planar Surface Segments Detected by a 3D Camera

Cupec, Robert; Nyarko, Emmanuel Karlo; Filko, Damir; Kitanov, Andrej; Petrović, Ivan

doi:10.20532/ccvw.2013.0008

Cited by 6 publications

(6 citation statements)

References 16 publications

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“…The uncertainty of g depends on the uncertainty of n i as well as on its orientation. The uncertainty of n i is estimated using the approach described in [33]. Covariance matrix p of all points belonging to the considered patch is computed.…”

Section: Vision-based Simple Objects Grasp Planningmentioning

confidence: 99%

Visual servoing for low-cost SCARA robots using an RGB-D camera as the only sensor

2017

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Visual servoing with a simple, two-step hand-eye calibration for robot arms in Selective Compliance Assembly Robot Arm configuration, along with the method for simple vision-based grasp planning, is proposed. The proposed approach is designed for low-cost, vision-guided robots, where tool positioning is achieved by visual servoing using marker tracking and depth information provided by an RGB-D camera, without encoders or any other sensors. The calibration is based on identification of the dominant horizontal plane in the camera field of view, and an assumption that all robot axes are perpendicular to the identified plane. Along with the plane parameters, one rotational movement of the shoulder joint provides sufficient information for visual servoing. The grasp planning is based on bounding boxes of simple objects detected in the RGB-D image, which provide sufficient information for robot tool positioning, gripper orientation and opening width. The developed methods are experimentally tested using a real robot arm. The accuracy of the proposed approach is analysed by measuring the positioning accuracy as well as by performing grasping experiments.

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Section: Vision-based Simple Objects Grasp Planningmentioning

confidence: 99%

Visual servoing for low-cost SCARA robots using an RGB-D camera as the only sensor

2017

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“…However, those methods are usually very slow. Some researchers also try to use 3D planes as the global map to locate the robot (Cupec, Nyarko, Filko, Kitanov, & Petrović, ; Fallon, Johannsson, & Leonard, ). For example, Fallon et al.…”

Section: Related Workmentioning

confidence: 99%

Robust Autonomous Flight in Constrained and Visually Degraded Shipboard Environments

Fang

Yang

Jain

et al. 2016

Journal of Field Robotics

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This paper addresses the problem of autonomous navigation of a micro aerial vehicle (MAV) for inspection and damage assessment inside a constrained shipboard environment, which might be perilous or inaccessible for humans, especially in emergency scenarios. The environment is GPS‐denied and visually degraded, containing narrow passageways, doorways, and small objects protruding from the wall. This causes existing two‐dimensional LIDAR, vision, or mechanical bumper‐based autonomous navigation solutions to fail. To realize autonomous navigation in such challenging environments, we first propose a robust state estimation method that fuses estimates from a real‐time odometry estimation algorithm and a particle filtering localization algorithm with other sensor information in a two‐layer fusion framework. Then, an online motion‐planning algorithm that combines trajectory optimization with a receding horizon control framework is proposed for fast obstacle avoidance. All the computations are done in real time on the onboard computer. We validate the system by running experiments under different environmental conditions in both laboratory and practical shipboard environments. The field experiment results of over 10 runs show that our vehicle can robustly navigate 20‐m‐long and only 1‐m‐wide corridors and go through a very narrow doorway (66‐cm width, only 4‐cm clearance on each side) autonomously even when it is completely dark or full of light smoke. These experiments show that despite the challenges associated with flying robustly in challenging shipboard environments, it is possible to use a MAV to autonomously fly into a confined shipboard environment to rapidly gather situational information to guide firefighting and rescue efforts.

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“…The proposed method builds upon the approach presented by Cupec et al (2012Cupec et al ( , 2013. In this paper, an improved approach is presented, which includes application of line segment features as well as a novel probabilistic hypothesis evaluation method based on surface sampling.…”

Section: Related Researchmentioning

confidence: 99%

“…These variances are computed from the uncertainties of the supporting point positions, which are determined using a triangulation uncertainty model analogous to the one proposed by Matthies and Shafer (1987). Computation of covariance matrices S q is explained by Cupec et al (2013).…”

Section: Detection and Representation Of Surface Segmentsmentioning

confidence: 99%

“…Many samples classified as invisible in the top right-hand image in Figure 10 indicate that only a relatively small part of the scene overlaps with the corresponding local model. The approach presented in this paper is based on the approach proposed by Cupec et al (2012Cupec et al ( , 2013. There are three main improvements to the original method: 1. in addition to the planar surface segments, line segment features are used in the hypothesis generation process; 2. instead of approximating the surface segments by ellipsoids, each surface segment is represented by a set of samples, which should provide a better description of the surface shape, and a novel probabilistic hypothesis evaluation approach is used to select the best hypothesis; 3. a mechanism for detection and rejection of dynamic surfaces is introduced.…”

Section: Robustness To Changing Environmentmentioning

confidence: 99%

See 1 more Smart Citation

Place recognition based on matching of planar surfaces and line segments

Cupec

Nyarko

Filko

et al. 2015

The International Journal of Robotics Research

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This paper considers the potential of using three-dimensional (3D) planar surfaces and line segments detected in depth images for place recognition. A place recognition method is presented that is based on matching sets of surface and line features extracted from depth images provided by a 3D camera to features of the same type contained in a previously created environment model. The considered environment model consists of a set of local models representing particular locations in the modeled environment. Each local model consists of planar surface segments and line segments representing the edges of objects in the environment. The presented method is designed for indoor and urban environments. A computationally efficient pose hypothesis generation approach is proposed that ranks the features according to their potential contribution to the pose information, thereby reducing the time needed for obtaining accurate pose estimation. Furthermore, a robust probabilistic method for selecting the best pose hypothesis is proposed that allows matching of partially overlapping point clouds with gross outliers. The proposed approach is experimentally tested on a benchmark dataset containing depth images acquired in the indoor environment with changes in lighting conditions and the presence of moving objects. A comparison of the proposed method to FAB-MAP and DLoopDetector is reported.

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Global Localization Based on 3D Planar Surface Segments Detected by a 3D Camera

Cited by 6 publications

References 16 publications

Visual servoing for low-cost SCARA robots using an RGB-D camera as the only sensor

Visual servoing for low-cost SCARA robots using an RGB-D camera as the only sensor

Robust Autonomous Flight in Constrained and Visually Degraded Shipboard Environments

Place recognition based on matching of planar surfaces and line segments

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