Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Grasping: Modeling, Analysis and Planning
On the Caging Region of a Third Finger with Object Boundary Clouds and Two Given Contact PositionsThis paper presents a caging approach which deals with planar boundary clouds collected from a laser scanner. Given the boundary clouds of a target object and two fixed finger positions, our aim is to find potential third finger positions that can prevent target from escaping into infinity. The major challenge in working with boundary clouds lies in their uncertainty in geometric model fitting and the failure of critical orientations. In this paper, we track canonical motions according to the rotational intersection of Configuration space fingers and rasterize Work space with grids to compute the third caging positions. Our approach can generate the capture region with max(O(np),O(h^2))<=O(n^2) cost where n denotes the resolution of grid rasterization, p denotes the resolution of canonical rasterization and h denotes the resolution of boundary rasterization or the number of boundary cloud points. Moreover, we propose a rough approximation which measures a subset of the possible positions by contracting rotations, indicating computational complexity of max(O(n),O(h^2)). In the experimental part, our proposal is compared with state-of-the-art works and applied to many other objects. The approach makes caging fast and effective.
Independent Contact Regions Based on a Patch Contact ModelThe synthesis of multi-fingered grasps on non-trivial objects requires a realistic representation of the contact between the fingers of a robotic hand and an object. In this work, we use a patch contact model to approximate the contact between a rigid object and a deformable anthropomorphic finger. This contact model is utilized in the computation of Independent Contact Regions (ICRs) that have been proposed as a way to compensate for shortcomings in the finger positioning accuracy of robotic grasping devices. We extend the ICR algorithm to account for the patch contact model and show the benefits of this solution.
A Grasping Force Optimization Algorithm for Dexterous Robotic HandsThe problem of grasping force optimization for a robotic system equipped with multi-fingered hands is considered in this paper. This problem is cast in a convex optimization problem, considering also joint torque constraints. A solution suitable for an online implementation, which allows a substantial reduction of the computational load by dynamically decreasing the number of active torque constraints is proposed. Moreover, for the case of a bimanual manipulation system, a sub-optimal single-hand optimization algorithm is presented and compared with the optimal one. The effectiveness of the described methods has been tested in a simulation case study.
Local Force ClosureWe introduce the concept of Local Force Closure. We define a local force closure grasp as a grasp which is capable of resisting some given external wrench as well as (through local variation in contact wrenches) any wrench in some neighborhood of the given wrench, with grasp quality exceeding some given threshold. Local force closure is useful in applications where a grasp only needs to resist some given external wrench, rather than fully constraining object, but where there is some uncertainty regarding the exact external wrench that needs to be resisted, or where there is a possibility of having to cope with some (relatively small) unknown disturbance forces. We show that by allowing disc-shaped fingers in contact with convex vertices of a polygonal object, any given wrench can be resisted by just two frictionless fingers. For a given polygonal object with <i>n</i> vertices and an external wrench <i>w</i><sub>ext</sub>, we show how to find all pairs of features of <i>P</i>, that admit grasps capable of resisting <i>w</i><sub>ext</sub> with grasp quality greater or equal to some threshold <i>Q</i>, in <i>O(n<sup>3/2+ε</sup>+K)</i> time, where <i>K</i> is the number of pairs in the output and <i>ε</i> is some arbitrarily small, positive constant. We then show how to adapt our algorithm to guarantee that the features reported, admit local force closure grasps.
Two-Fingered Caging of Polygons Via Contact-Space Graph SearchBased on a novel contact-space formulation, this paper presents a new algorithm to find two-fingered caging grasps of planar polygonal objects. We show that the caging problem has several useful properties in contact space. First, the critical points of the cage representation in the handâ€™s configuration space appear as critical points of an inter-finger distance function in contact space. Second, the critical points of this distance function can be simply characterized. Third, the contact space admits a rectangular decomposition where the distance function is convex in each rectangle, and all critical points lie on the rectangle boundaries. This property leads to a natural â€œcaging graph,â€ which can be readily searched to construct the caging sets. An example, constructed from real-world data illustrates and validates the method.
Object Categorization and Grasping by Parts from Range Scan DataObject category recognition and localization in 3D range data is of great importance in robot manipulation. In this work we propose a novel approach for object categorization and grasping that is focused on topological shape segmentation. The method allows generation of watertight triangulated models of the objects and their shape segmentation into parts. This segmentation provides meaningful information about grasp affordances. An efficient technique for encoding proximity data from range scans is also presented as well as an advanced strategy for manipulation of object sub-parts. Experiments are reported in a real environment using a robot arm equipped with eye-in-hand laser scanner and a parallel gripper.