Jan Rosell

Path planning using Harmonic Functions and Probabilistic Cell Decomposition

Potential-field approaches based on harmonic functions have good path planning properties, although the explicit knowledge of the robot’s Configuration Space is required. To overcome this drawback, a combination with a random sampling scheme is proposed. Harmonic functions are computed over a 2 d-tree decomposition of a d-dimensional Configuration Space that is obtained with a probabilistic cell decomposition (sampling and classification). Cell sampling is biased towards the more promising regions by using the harmonic function values. Cell classification is performed by evaluating a set of configurations of the cell obtained with a deterministic sampling sequence that provides a good uniform and incremental coverage of the cell. The proposed planning framework opens the use of harmonic functions to higher dimensional C-spaces.

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

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.

Motion Planning for Haptic Guidance

Haptic devices allow a user to feel either reaction forces from virtual interactions or reaction forces reflected from a remote site during a bilateral teleoperation task. Also, guiding forces can be exerted to train the user in the performance of a virtual task or to assist him/her to safely teleoperate a robot. The generation of guiding forces relies on the existence of a motion plan that provides the direction to be followed to reach the goal from any free configuration of the configuration space (

Haptic-based navigation for the virtual bronchoscopy

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Assembly and task planning using Petri nets: A survey

-space). This paper proposes a method to obtain such a plan that interleaves a sampling-based exploration of

A General Deterministic Sequence for Sampling d-Dimensional Configuration Spaces

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A roadmap to robot motion planning software development

-space with an efficient computation of harmonic functions. A deterministic sampling sequence (with a bias based on harmonic function values) is used to obtain a hierarchical cell decomposition model of

A hierarchical and dynamic method to compute harmonic functions for constrained motion planning

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Robotic polishing systems

-space. A harmonic function is iteratively computed over the partially known model using a novel approach. The harmonic function is the navigation function used as motion plan. The approach has been implemented in a planner (called the Kautham planner) that, given an initial and a goal configuration, provides: (a) a channel of cells connecting the cell that contains the initial configuration with the cell that contains the goal configuration; (b) two harmonic functions over the whole

Using configuration and force sensing in assembly task planning and execution

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