Systems integration for real-world manipulation tasks

Tell, Dennis; Strandberg, Morten Tune; Kragić, Danica; Christensen, Henrik I.

doi:10.1109/robot.2002.1013607

Cited by 30 publications

(27 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A different set of underlying visual strategies are required for each of these scenarios being the most representative examples for robotic fetch-and-carry tasks. We have worked with different aspects of the above for the past several years, (Björkman and Eklundh, 2002;Björkman and Eklundh, 2006;Björkman and Kragic, 2004;Ekvall and Kragic, 2005;Ekvall et al, 2007;Huebner et al, 2008a;Kragic and Kyrki, 2006;Petersson et al, 2002;Rasolzadeh et al, 2006Rasolzadeh et al, , 2007Topp et al, 2004). The work presented here continues our previous works, but the focus is put on the design and development of a vision system architecture for the purpose of solving more complex visual tasks.…”

Section: Introductionmentioning

confidence: 92%

An Active Vision System for Detecting, Fixating and Manipulating Objects in the Real World

Rasolzadeh¹,

Björkman²,

Huebner³

et al. 2009

The International Journal of Robotics Research

Self Cite

View full text Add to dashboard Cite

The ability to autonomously acquire new knowledge through interaction with the environment is an important research topic in the field of robotics. The knowledge can be acquired only if suitable perception-action capabilities are present: a robotic system has to be able to detect, attend to and manipulate objects in its surrounding. In this paper, we present the results of our longterm work in the area of vision based sensing and control. The work on finding, attending, recognizing and manipulating objects in domestic environments is studied. We present a stereo based vision system framework where aspects of Top-down and Bottom-up attention as well as foveated attention are put into focus and demonstrate how the system can be utilized for robotic object grasping.

show abstract

Section: Introductionmentioning

confidence: 92%

An Active Vision System for Detecting, Fixating and Manipulating Objects in the Real World

Rasolzadeh¹,

Björkman²,

Huebner³

et al. 2009

The International Journal of Robotics Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…The vision system design is based on the active vision paradigm, [1] where, instead of passively observing the world, viewing conditions are actively changed so that the best results are obtained given the task at hand. In our previous work [24], we showed how the robot can grasp objects given that the object is in front of the robot and the camera is centered on the object. With the work presented in this paper, those assumptions can be ignored.…”

Section: Motivation and Related Workmentioning

confidence: 99%

“…Both of the above have strongly influenced our current work where the integration of object recognition and map building represents a basis for longterm reasoning and planning in an autonomous robot system. Some of our previous contributions related to different parts of a service robot system have been presented in [10,13,[23][24][25]32].…”

Section: Introductionmentioning

confidence: 99%

Object detection and mapping for service robot tasks

2007

View full text Add to dashboard Cite

The problem studied in this paper is a mobile robot that autonomously navigates in a domestic environment, builds a map as it moves along and localizes its position in it. In addition, the robot detects predefined objects, estimates their position in the environment and integrates this with the localization module to automatically put the objects in the generated map. Thus, we demonstrate one of the possible strategies for the integration of spatial and semantic knowledge in a service robot scenario where a simultaneous localization and mapping (SLAM) and object detection/recognition system work in synergy to provide a richer representation of the environment than it would be possible with either of the methods alone.Most SLAM systems build maps that are only used for localizing the robot. Such maps are typically based on grids or different types of features such as point and lines. The novelty is the augmentation of this process with an object recognition system that detects objects in the environment and puts them in the map generated by the SLAM system. The metric map is also split into topological entities corresponding to rooms. In this way the user can command the robot to retrieve a certain object from a certain room. We present the results of map building and an extensive evaluation of the object detection algorithm performed in an indoor setting.

show abstract

“…A system integration aspect of mobile manipulation was recently presented by L. Petersson [5] , where the components of the PNP operation are rigorously treated to find optimal order of execution. T. Takahama presented motion planning and system integration algorithms for a mobile robot with dual manipulators for the specific task of arranging books in a bookcase [6] .…”

Section: Introduction1 )mentioning

confidence: 99%

Pose Selection of a Mobile Manipulator for a Pick and Place Task

Cho¹

2011

The Journal of Korea Robotics Society

View full text Add to dashboard Cite

A mobile manipulator is a system with a robotic manipulator mounted on top of a mobile base. It has both indoor and outdoor applications for transporting or transferring materials. When a user gives commands, they are usually at high levels such as "move the object to the table," or "tidy the room." By intelligently decomposing these complex commands into several subtasks, the mobile manipulator can perform the tasks with a greater efficiency. One of the crucial subtasks for these commands is the pick-and-place task. For the mobile manipulator, selection of a good base position and orientation is essential to accomplishing this task. This paper presents an algorithm that determines one of the position and orientation of a mobile manipulator in order to complete the pickand-place task without human intervention. Its effectiveness are shown for a mobile manipulator with 9 degrees-of-freedom in simulations

show abstract

Systems integration for real-world manipulation tasks

Cited by 30 publications

References 5 publications

An Active Vision System for Detecting, Fixating and Manipulating Objects in the Real World

An Active Vision System for Detecting, Fixating and Manipulating Objects in the Real World

Object detection and mapping for service robot tasks

Pose Selection of a Mobile Manipulator for a Pick and Place Task

Contact Info

Product

Resources

About