On the use of scaling matrices for task-specific robot design

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

doi:10.1109/70.795800

Cited by 66 publications

(31 citation statements)

References 11 publications

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“…By choosing the elements of S J as free design parameters, the optimum robot geometry and actuator sizes are identified simultaneously. This has been shown in [25] to significantly improve robot performance, particularly with serial mechanisms.…”

Section: Design Proceduresmentioning

confidence: 99%

“…The matrix normalizing technique described in [25] is applied to the GII to obtain the workspace-inclusive, unitless, task-dependent performance measure shown in equation (11) where and are the minimum and maximum singular values of the Jacobian J(p,x) which is computed for a design parameter p at a position x in the workspace W and is scaled by matrices S J (12) and S T (13) which are diagonal matrices containing the maximum torque capabilities τ 1 ...τ n of each actuator (for a robot with n actuators) and the maximum required end-effector forces F and moments M about axes , and . …”

Section: Design Proceduresmentioning

confidence: 99%

“…Section III describes two biomechanics studies that are conducted to obtain force and velocity values to guide the kinematic design and sensor selection processes. In Section IV, a design procedure is summarized which was previously developed by the authors in [24] and [25]. It selects the geometric parameters and actuator scale factors that best satisfy a direction dependent performance criteria inside a pre-defined operational workspace.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal kinematic design of a haptic pen

Stocco

Salcudean

Sassani

2001

IEEE/ASME Trans. Mechatron.

Self Cite

100

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Section: Design Proceduresmentioning

confidence: 99%

Section: Design Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal kinematic design of a haptic pen

Stocco

Salcudean

Sassani

2001

IEEE/ASME Trans. Mechatron.

Self Cite

100

View full text Add to dashboard Cite

“…While some comparison of the length scales of the task and environment have been used to inform the geometry and design of robotic platforms in the past [2] [3], generalizing this concept could prove useful for evaluating the fitness of preexisting robotic architectures, inviting the concepts of 'quasi-static mismatch' and 'dynamic mismatch'. Quasi-static mismatch, the inability of a robot to perform a task in a given environment using quasi-static methods, stems from either geometric constraints or inadequate thermally continuous torque density, while dynamic mismatch arises from insufficient energy or power density.…”

Section: Introductionmentioning

confidence: 99%

Quasi-static and dynamic mismatch for door opening and stair climbing with a legged robot

Topping

Kenneally

Koditschek

2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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This paper contributes to quantifying the notion of robotic fitness by developing a set of necessary conditions that determine whether a small quadruped has the ability to open a class of doors or climb a class of stairs using only quasi-static maneuvers. After verifying that several such machines from the recent robotics literature are mismatched in this sense to the common human scale environment, we present empirical workarounds for the Minitaur quadrupedal platform that enable it to leap up, force the door handle and push through the door, as well as bound up the stairs, thereby accomplishing through dynamical maneuvers otherwise (i.e., quasi-statically) achievable tasks. Abstract-This paper contributes to quantifying the notion of robotic fitness by developing a set of necessary conditions that determine whether a small quadruped has the ability to open a class of doors or climb a class of stairs using only quasi-static maneuvers. After verifying that several such machines from the recent robotics literature are mismatched in this sense to the common human scale environment, we present empirical workarounds for the Minitaur quadrupedal platform that enable it to leap up, force the door handle and push through the door, as well as bound up the stairs, thereby accomplishing through dynamical maneuvers otherwise (i.e., quasi-statically) unachievable tasks.

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“…This assertion is investigated extensively and proved in [36,55,56,60,61]. Therefore, two separate performance indices are considered for the purpose of this paper, namely point-displacement and rotational kinematic sensitivity, which have been recently proposed to the end of alleviating the limitations of the above notorious indices [55].…”

Section: Review Of the Case-study: Moo Of The Point-displacement And mentioning

confidence: 99%

PPCOF: A Robust Proportion-Preserving Composite Objective Function for Scale-Invariant Multi-Objective Optimization

et al. 2017

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Abstract. This paper aims to introduce a proportion-preserving composite objective function for multi-objective optimization, namely, PPCOF, and validate its e ciency through demonstrating its applicability to optimization of the kinetostatic performance of planar parallel mechanisms. It exempts the user from both specifying preference factors and conducting decision-making. It consists of two terms. The rst one adds the normalized objective functions up, where the extrema result from single-objective optimization. To make the composite objective function steer the variations of the objective functions while preserving rational proportions between them, as the main contribution of the paper, it is sought that the normalized objective functions take closely similar values, to which end they are juxtaposed inside a vector, which is then scaled such that its Euclidean norm-2 is equal to that of the vector of all ones with the same dimensions. Then, the second term is constructed as the addition of penalty factors standing for the absolute value of the di erence between each element of the foregoing vector from 1. From the obtained results, with considerably smaller computational cost, the PPCOF obtains an optimal solution that is not dominated by any point from a set of Pareto-optimal solutions o ered by NSGA-II.

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On the use of scaling matrices for task-specific robot design

Cited by 66 publications

References 11 publications

Optimal kinematic design of a haptic pen

Optimal kinematic design of a haptic pen

Quasi-static and dynamic mismatch for door opening and stair climbing with a legged robot

PPCOF: A Robust Proportion-Preserving Composite Objective Function for Scale-Invariant Multi-Objective Optimization

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