A clickable world: Behavior selection through pointing and context for mobile manipulation

Nguyen, Hai; Jain, Abhinav; Anderson, Cressel; Kemp, Charles C.

doi:10.1109/iros.2008.4651216

Cited by 45 publications

(26 citation statements)

References 5 publications

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“…By referring the chair model from the database related to the ID, the detection of handling point on the chair is discussed based on the RFID and the LRF. In [6], a behavior selection system for human-robot interaction of the mobile manipulator El-E is presented. This system has a laser-pointer interface.…”

Section: Target Object Identification and Localization In Mobile Manimentioning

confidence: 99%

Target object identification and localization in mobile manipulations

Jiang

Zhang

et al. 2011

2011 IEEE International Conference on Robotics and Biomimetics

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Abstract-How to make mobile manipulator autonomously identify and locate target object in unknown environment, this is a very challenging question. In this paper, a multi-sensor fusion method based on camera and laser range finder (LRF) for mobile manipulations is proposed. Although the camera can acquire rich perceptual information, the image processing is very complex and easily influenced from the change in ambient light. Moreover, it can not directly provide the depth information of the environment. Since the LRF has the ability to directly measure 3D coordinates and the stability against the ambient light influence, meanwhile, the camera has the ability to acquire color information, the combination of the two sensors by making use of their advantages is utilized to obtain more accurate measurements as well as to simplify information processing. To overlay the camera image with the measurement points of the LRF pitching scan and to reconstruct the 3D image which includes the depth-of-field information, the model and the calibration of the system are built. Based on the combination of the color features extracted from the color image and the shape, size features extracted from the 3D depth-of-field image, the target object identification and localization are implemented autonomously. In order to extract the shape and size features, a triangular facet normal vector clustering (TFNVC) algorithm is introduced. The effectiveness of the proposed method and algorithm are validated by some experimental testing and analysis carried out on the mobile manipulator platform.

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Section: Target Object Identification and Localization In Mobile Manimentioning

confidence: 99%

Target object identification and localization in mobile manipulations

Jiang

Zhang

et al. 2011

2011 IEEE International Conference on Robotics and Biomimetics

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“…We have previously presented results related to EL-E's user interface and method of behavior selection Nguyen et al 2008b). We have also reported results on This figure shows the servo tilting the laser range finder to generate a 3D point cloud a user study in which patients from the Emory ALS 1 Center successfully designated objects for EL-E to pick up (Choi et al 2008).…”

Section: Prior Research With El-ementioning

confidence: 99%

EL-E: an assistive mobile manipulator that autonomously fetches objects from flat surfaces

2009

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Assistive mobile robots that autonomously manipulate objects within everyday settings have the potential to improve the lives of the elderly, injured, and disabled. Within this paper, we present the most recent version of the assistive mobile manipulator EL-E with a focus on the subsystem that enables the robot to retrieve objects from and deliver objects to flat surfaces. Once provided with a 3D location via brief illumination with a laser pointer, the robot autonomously approaches the location and then either grasps the nearest object or places an object. We describe our implementation in detail, while highlighting design principles and themes, including the use of specialized behaviors, taskrelevant features, and low-dimensional representations.We also present evaluations of EL-E's performance relative to common forms of variation. We tested EL-E's ability to approach and grasp objects from the 25 object categories that were ranked most important for robotic retrieval by motor-impaired patients from the Emory ALS Center. Although reliability varied, EL-E succeeded at least once with objects from 21 out of 25 of these categories. EL-E also approached and grasped a cordless telephone on 12 different surfaces including floors, tables, and counter tops with 100% success. The same test using a vitamin pill (ca. 15 mm × 5 mm × 5 mm) resulted in 58% success.

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“…Novel human-robot interfaces such as virtual button activated by pointing an off-the-shelf green laser pointer were proposed [31].…”

Section: Introductionmentioning

confidence: 99%

Challenges and Solutions for Autonomous Robotic Mobile Manipulation for Outdoor Sample Collection

Cui¹

2015

JEEE

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Abstract:In refinery, petrochemical, and chemical plants, process technicians collect uncontaminated samples to be analyzed in the quality control laboratory all time and all weather. This traditionally manual operation not only exposes the process technicians to hazardous chemicals, but also imposes an economical burden on the management. The recent development in mobile manipulation provides an opportunity to fully automate the operation of sample collection. This paper reviewed the various challenges in sample collection in terms of navigation of the mobile platform and manipulation of the robotic arm from four aspects, namely mobile robot positioning/attitude using global navigation satellite system (GNSS), vision-based navigation and visual servoing, robotic manipulation, mobile robot path planning and control. This paper further proposed solutions to these challenges and pointed the main direction of development in mobile manipulation.

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A clickable world: Behavior selection through pointing and context for mobile manipulation

Cited by 45 publications

References 5 publications

Target object identification and localization in mobile manipulations

Target object identification and localization in mobile manipulations

EL-E: an assistive mobile manipulator that autonomously fetches objects from flat surfaces

Challenges and Solutions for Autonomous Robotic Mobile Manipulation for Outdoor Sample Collection

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