Path planning for grasping operations using an adaptive PCA-based sampling method

Rosell, Jan; Suárez, Raúl; Pérez, Alexander

doi:10.1007/s10514-013-9332-5

Cited by 14 publications

(11 citation statements)

References 25 publications

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“…The Kautham Project has been used for the development of many planners related to the motion of hand-arm robotic systems, like those reported in [19][23] [24] [25], that reproduce in the mechanical hand the coupling between the motion of the fingers of the human hand. In a different scope, it has been used within a virtual bronchoscopy system for the motion planning of a bronchoscope (with kinematic constraints) from the trachea to a peripheral lung lesion [26].…”

Section: B Researchmentioning

confidence: 99%

The Kautham project: A teaching and research tool for robot motion planning

Rosell

Pérez

Akbari

et al. 2014

Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)

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Abstract-This paper presents the software tool used at the Institute of Industrial and Control Engineering (IOC-UPC) for teaching and research in robot motion planning. The tool allows to cope with problems with one or more robots, being a generic robot defined as a kinematic tree with a mobile base, i.e. the tool can plan and simulate from simple two degrees of freedom free-flying robots to multi-robot scenarios with mobile manipulators equipped with anthropomorphic hands. The main core of planners is provided by the Open Motion Planning Library (OMPL). Different basic planners can be flexibly used and parameterized, allowing students to gain insight into the different planning algorithms. Among the advanced features the tool allows to easily define the coupling between degrees of freedom, the dynamic simulation and the integration with task planers. It is principally being used in the research of motion planning strategies for hand-arm robotic systems.

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Section: B Researchmentioning

confidence: 99%

The Kautham project: A teaching and research tool for robot motion planning

Rosell

Pérez

Akbari

et al. 2014

Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)

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“…Samples of potential hand positions are taken inside this space, and an adaptive sampling method based on PCA is applied to bias the sampling towards promising areas. This follows the idea proposed in [25], where the PCA guides the sampling process in path planning problems with narrow passages by adapting the region in the configuration space from where the next sample is taken.…”

Section: Using Pcamentioning

confidence: 99%

“…It is important to notice that the PCA method in this case does not try to apply any dimension reduction to the space, but just guides the sampling process towards promising areas. A similar approach has been used in [25] to guide the sampling process in narrow passages for motion planning.…”

Section: Using Pcamentioning

confidence: 99%

Integrated grasp and motion planning using independent contact regions

Fontanals

Dang-Vu

Porges

et al. 2014

2014 IEEE-RAS International Conference on Humanoid Robots

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Traditionally, grasp and arm motion planning are considered as separate tasks. This might lead to problems such as limitations in the grasp possibilities, or unnecessary long times in the solution of the planning problem. This thesis presents an integrated approach that only requires the initial configuration of the robotic arm and the pose of the target object to simultaneously plan a good hand pose and arm trajectory to grasp the object.The planner exploits the concept of independent contact regions to look for the best possible grasp. In this document, two different methods have been considered to search for good end-effector poses. One biases a sampling approach towards favorable regions using principal component analysis, and the other one considers the capabilities of the robotic arm to decide the most promising hand poses. The performance of the methods is evaluated using different scenarios for the humanoid robot SpaceJustin. In order to validate the paths, some scenarios were replicated in the laboratory and the generated paths were executed on the real robot.

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“…configuration-space costmaps [8], or to bias the sampling towards better regions of the configuration space by using, for instance, retraction-based methods [9] or Principal Component Analysis (PCA) [10]. Since these algorithms are non-optimal, other variants like the PRM * and RRT * algorithms have been proposed [11].…”

Section: Introductionmentioning

confidence: 99%

Motion Planning by Demonstration With Human-Likeness Evaluation for Dual-Arm Robots

Garcia

Rosell

Suárez

2019

IEEE Trans. Syst. Man Cybern, Syst.

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Abstract-The paper presents a planning procedure that allows an anthropomorphic dual-arm robotic system to perform a manipulation task in a natural human-like way by using demonstrated human movements. The key idea of the proposal is to convert the demonstrated trajectories into attractive potential fields defined over the configuration space and then use an RRT * -based planning algorithm that minimizes a path-cost function designed to bias the tree growth towards the human-demonstrated configurations. The paper presents a description of the proposed approach as well as results from a conceptual and a real application example, the latter using a real anthropomorphic dual-arm robotic system. A path-quality measure, based on first-order synergies (correlations between joint velocities) obtained from real human movements, is also proposed and used for evaluation and comparison purposes. The obtained results show that the paths obtained with the proposed procedure are more human-like.

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Path planning for grasping operations using an adaptive PCA-based sampling method

Cited by 14 publications

References 25 publications

The Kautham project: A teaching and research tool for robot motion planning

The Kautham project: A teaching and research tool for robot motion planning

Integrated grasp and motion planning using independent contact regions

Motion Planning by Demonstration With Human-Likeness Evaluation for Dual-Arm Robots

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