Fast constrained global minimax optimization of robot parameters

Stocco, Leo; Salcudean, Septimiu E.; Sassani, Farrokh

doi:10.1017/s0263574798000435

Cited by 111 publications

(96 citation statements)

References 34 publications

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“…With the goal to obtain a global measure for the isotropy movement, Stocco et al [101] optimized the ratio of the global maximum and the global minimum singular value of the Jacobian in the entire workspace to obtain a global version of the condition number. However, the smallest singular value varies radically in the presence of singularities thus dominating the behavior of the condition number and the determinant.…”

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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Section: Analysis Of the Jacobian Matrixmentioning

confidence: 99%

Knowledge Representations for Planning Manipulation Tasks

Zacharias

2012

Cognitive Systems Monographs

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“…Optimization techniques are used to determine the smallest inertial properties and the maximum achievable acceleration of the end-effector in every direction over the workspace. A global isotropy index has been proposed to quantify a configuration independent isotropy of a robot's Jacobian or mass matrix, [11]. This index was used to compare the performance of three manipulators, including two parallel platform robots and a hybrid robot, [12].…”

Section: Introductionmentioning

confidence: 99%

Mass/inertia and joint friction minimization for a low-force five-dof haptic device

Vlachos

Papadopoulos

Mitropoulos

2004

IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004

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Abstract-This paper presents a design methodology, which aims at the minimization of the mass, inertia and joint friction for a low -force five -dof haptic device. The haptic device is optimized along a typical path with proper tolerances, rather than at some workspace operating point. The device, part of a training medical simulator for urological operations, consists of a two dof, 5-bar linkage and a three dof spherical joint. The requirement for reliable reproduction of low torques and forces lead to the need for minimization of device induced parasitic forces and torques. The multiobjective optimization employed is based on two objective functions that include mass/ inertia properties and joint friction. Kinematical and operational constraints are taken into account. The resulting optimized mechanism is substantially improved with respect to an existing device.

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“…bound methods (Stocco et al, 1998) have been applied to design optimization of parallel mechanisms. In general, deterministic methods can get stuck at a local optimum, heuristic methods cannot guarantee optimality of the converged solution, while branch and bound type methods are only as accurate as the discretization selected.…”

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confidence: 99%

“…Among these approaches, Hayward et al define the relationship between multiple criteria and utilize sensitivities of these criteria to conduct a hierarchical optimization study (Hayward et al, 1994). Multiple objectives are considered sequentially in (Alici & Shirinzadeh, 2004;Krefft et al, 2005;Risoli et al, 1999;Stocco et al, 1998) by searching for parameter sets resulting in near optimal kinematic performance and then selecting the design exhibiting the best dynamic performance from this reduced parameter space. Task-priority (Chen et al, 1995), probabilistic weighting (McGhee et al, 1994), composite index (Lee et al, 2001), and tabular methods (Yoon & Ryu, 2001) are among the other scalarization approaches that consider multiple criteria.…”

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confidence: 99%

“…Global kinematic and dynamic performance of parallel mechanisms defined over a pre-specified singularity free workspace are maximized simultaneously and the Pareto-front curve for these two criteria is obtained. Firstly, the global optima of non-convex min-max performance criteria are solved independently from each other, using a modified branch and bound algorithm, called culling algorithm (Stocco et al, 1998). Once optimal solutions of each single criteria optimization problem are obtained, Normal Boundary Intersection (NBI) method (Das & Dennis, 1996), which performs a deterministic geometric search within the objective space, is utilized to efficiently compute uniformly distributed design solutions on the Pareto-front curve.…”

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confidence: 99%

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