On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

Autonomous dexterous end-effectors for space robotics

The development of a knowledge-based controller is summarized for the Belgrade/USC robot hand, a five-fingered end effector, designed for maximum autonomy. The biological principles of the hand and its architecture are presented. The conceptual and software aspects of the grasp selection system are discussed, including both the effects of the geometry of the target object and the task to be performed. Some current research issues are presented

Ground Robotic Hand Applications for the Space Program study (GRASP)

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time

Gross motion analysis of fingertip-based within-hand manipulation

Fingertip-based within-hand manipulation, also called precision manipulation, refers to the repositioning of a grasped object within the workspace of a multi-fingered robot hand without breaking or changing the contact type between each fingertip and the object. Given a robot hand architecture and a set of assumed contact models, this paper presents a method to perform a gross motion analysis of its precision manipulation capabilities, regardless of the particularities of the object being manipulated. In particular, the technique allows the composition of the displacement manifold of the grasped object relative to the palm of the robot hand to be determined as well as the displacements that can be controlled—useful for high-level design and classification of hand function. The effects of a fingertip contacting a body in this analysis are modeled as kinematic chains composed of passive and resistant revolute joints; what permits the introduction of a general framework for the definition and classification of non-frictional and frictional contact types. Examples of the application of the proposed method in several architectures of multi-fingered hands with different contact assumptions are discussed; they illustrate how inappropriate contact conditions may lead to uncontrollable displacements of the grasped object

Analysis and Observations from the First Amazon Picking Challenge

This paper presents a overview of the inaugural Amazon Picking Challenge along with a summary of a survey conducted among the 26 participating teams. The challenge goal was to design an autonomous robot to pick items from a warehouse shelf. This task is currently performed by human workers, and there is hope that robots can someday help increase efficiency and throughput while lowering cost. We report on a 28-question survey posed to the teams to learn about each team's background, mechanism design, perception apparatus, planning and control approach. We identify trends in this data, correlate it with each team's success in the competition, and discuss observations and lessons learned based on survey results and the authors' personal experiences during the challenge

A Methodology for the Design of Robotic Hands with Multiple Fingers

This paper presents a methodology that has been applied for a design process of anthropomorphic hands with multiple fingers. Biomechanical characteristics of human hand have been analysed so that ergonomic and anthropometric aspects have been used as fundamental references for obtaining grasping mechanisms. A kinematic analysis has been proposed to define the requirements for designing grasping functions. Selection of materials and actuators has been discussed too. This topic has been based on previous experiences with prototypes that have been developed at the Laboratory of Robotics and Mechatronics (LARM) of the University of Cassino. An example of the application of the proposed method has been presented for the design of a first prototype of LARM Hand

Design of non-anthropomorphic robotic hands for anthropomorphic tasks

In this paper, we explore the idea of designing non- anthropomorphic multi-fingered robotic hands for tasks tha t replicate the motion of the human hand. Taking as input data a finite set of rigid-body positions for the five fingertips, we de- velop a method to perform dimensional synthesis for a kinema tic chain with a tree structure, with five branches that share thr ee common joints. We state the forward kinematics equations of relative dis- placements for each serial chain expressed as dual quaterni ons, and solve for up to five chains simultaneously to reach a numbe r of positions along the hand trajectory. This is done using a h y- brid global numerical solver that integrates a genetic algo rithm and a Levenberg-Marquardt local optimizer. Although the number of candidate solutions in this problem is very high, the use of the genetic algorithm allows us to per form an exhaustive exploration of the solution space to obtain a s et of solutions. We can then choose some of the solutions based on t he specific task to perform. Note that these designs match the ta sk exactly while generally having a finger design radically dif ferent from that of the human hand.Peer ReviewedPostprint (author’s final draft