Dexterity Measures for the Design and Control of Kinematically Redundant Manipulators

Klein, Charles A.; Blaho, Bruce E.

doi:10.1177/027836498700600206

Cited by 550 publications

(199 citation statements)

References 11 publications

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“…If the convex hull of the GWS contains the origin, it has closure, and any external wrench acting on the object can be resisted by a convex combination of the grasp wrenches. However, computing the convex hull at each simulation step is a computational bottleneck, and instead we estimate the grasp quality with an ellipsoid, similar to the method outlined by Klein and Baho [19]. The matrix G ∈ R 6×(mN) is assembled from a set of representative vectors, accounting for N fingerobject contacts and m basis vectors at each contact that approximate the Coulomb friction cone (as shown in Figure 4).…”

Section: Grasp Qualitymentioning

confidence: 99%

Goal directed multi-finger manipulation: Control policies and analysis

Andrews

Kry

2013

Computers & Graphics

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We present a method for one-handed, task-based manipulation of objects. Our approach uses a mid-level, multi-phase approach to organize the problem into three phases. This provides an appropriate control strategy for each phase and results in cyclic finger motions that, together, accomplish the task. The exact trajectory of the object is never specified since the goal is defined by the final orientation and position of the object. All motion is physically based and guided by a control policy that is learned through a series of offline simulations. We also discuss practical considerations for our learning method. Variations in the synthesized motions are possible by tuning a scalarized multi-objective optimization. We demonstrate our method with two manipulation tasks, discussing the performance and limitations. Additionally, we provide an analysis of the robustness of the low-level controllers used by our framework.

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Section: Grasp Qualitymentioning

confidence: 99%

Goal directed multi-finger manipulation: Control policies and analysis

Andrews

Kry

2013

Computers & Graphics

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“…In the following, several indices are described that have been derived thereof. Klein et al [50] examine dexterity measures with the aim to optimize the robot arm configuration for a given end-effector position. They analyze the relationship of the determinant, the condition number and the smallest singular value of the Jacobian.…”

Section: Analysis Of the Jacobian Matrixmentioning

confidence: 99%

Knowledge Representations for Planning Manipulation Tasks

Zacharias

2012

Cognitive Systems Monographs

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A complex manipulation task for a robot has to be planned on different levels of abstraction before it can be executed on a real system. At a high-level of abstraction, a task planner generates a sequence of subtasks from a given abstract command, its pre-and postconditions and a current world model. To restrict the already huge search space of the task planner, aspects like geometric information are not contained in the world model at this level. The task planner then assigns the subtasks to planners on a lower level of abstraction like path planners or grasp planners. These planners rely on geometric information to compute their solutions. However, without considering geometric information the task planner cannot determine good parameters for these low-level planners. Therefore, the derived plans may not be valid for a given situation and may require backtracking. Knowledge representations can bridge the gap between these planning levels and thereby enable scene reasoning. The kinematic capabilities of a robot are one aspect the task planner has to be aware of. Therefore this thesis introduces a novel general representation of the kinematic capabilities of a robot arm. The versatile workspace is defined to describe in which orientations the end effector attached to a robot arm can reach a position. The capability map is a calculable representation of the versatile workspace that allows to determine how well regions of the workspace are reachable. It accurately represents the versatile workspace of arbitrary arm kinematics and enables autonomous taskspecific reasoning. Furthermore, its visualization scheme is intuitively comprehensible for the human. The versatile applicability of the capability map is shown by examples from several distinct application domains. In human-robot interaction, the capability map is used to objectively evaluate a bi-manual interface for tele-operation. The results can also supplement the design process for humanoid robot design. In low-level geometric planning, the capability map is used to reduce the search space and to parameterize path planners and grasp planners. Thus, in a manipulation task for a humanoid robot more human-like motion is planned while simultaneously the computation time is reduced. In high-level task reasoning, the capability map is used to evaluate how well a robot is suited for a task. In an example a humanoid robot has to perform a task involving 3D trajectories. Regions are extracted from the capability map that permit the task execution and the suitability of the robot is inferred.

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“…The most common of these is perhaps the manipulability measure proposed by Yoshikawa ( 1984) that is defined as the square root of the determinant of the matrix Ji T, which is simply the product of the singular values of J. Other proposed measures include the trace of the above matrix (Baillieul 1987), the minimum singular value of the Jacobian (Klein and Blaho 1987), the compatibility index (Chiu 1987), and isotropy (all equal singular values; Salisbury and Craig 1982).…”

Section: Introductionmentioning

confidence: 99%