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

The GR2 gripper: an underactuated hand for open-loop in-hand planar manipulation

Performing dexterous manipulation of unknown objects with robot grippers without using high-fidelity contact sensors, active/sliding surfaces, or a priori workspace exploration is still an open problem in robot manipulation and a necessity for many robotics applications. In this paper, we present a two-fingered gripper topology that enables an enhanced predefined in-hand manipulation primitive controlled without knowing the size, shape, or other particularities of the grasped object. The in-hand manipulation behavior, namely, the planar manipulation of the grasped body, is predefined thanks to a simple hybrid low-level control scheme and has an increased range of motion due to the introduction of an elastic pivot joint between the two fingers. Experimental results with a prototype clearly show the advantages and benefits of the proposed concept. Given the generality of the topology and in-hand manipulation principle, researchers and designers working on multiple areas of robotics can benefit from the findings

The Coupler Surface of the RSRS Mechanism

Two degree-of-freedom (2-DOF) closed spatial linkages can be useful in the design of robotic devices for spatial rigid-body guidance or manipulation. One of the simplest linkages of this type, without any passive DOF on its links, is the revolutespherical-revolute-spherical (RSRS) four-bar spatial linkage. Although the RSRS topology has been used in some robotics applications, the kinematics study of this basic linkage has unexpectedly received little attention in the literature over the years. Counteracting this historical tendency, this work presents the derivation of the general implicit equation of the surface generated by a point on the coupler link of the general RSRS spatial mechanism. Since the derived surface equation expresses the Cartesian coordinates of the coupler point as a function only of known geometric parameters of the linkage, the equation can be useful, for instance, in the process of synthesizing new devices. The steps for generating the coupler surface, which is computed from a distance-based parametrization of the mechanism and is algebraic of order twelve, are detailed and a web link where the interested reader can download the full equation for further study is provided. It is also shown how the celebrated sextic curve of the planar four-bar linkage is obtained from this RSRS dodecic

Towards Generalized Robot Assembly through Compliance-Enabled Contact Formations

Contact can be conceptualized as a set of constraints imposed on two bodies that are interacting with one another in some way. The nature of a contact, whether a point, line, or surface, dictates how these bodies are able to move with respect to one another given a force, and a set of contacts can provide either partial or full constraint on a body's motion. Decades of work have explored how to explicitly estimate the location of a contact and its dynamics, e.g., frictional properties, but investigated methods have been computationally expensive and there often exists significant uncertainty in the final calculation. This has affected further advancements in contact-rich tasks that are seemingly simple to humans, such as generalized peg-in-hole insertions. In this work, instead of explicitly estimating the individual contact dynamics between an object and its hole, we approach this problem by investigating compliance-enabled contact formations. More formally, contact formations are defined according to the constraints imposed on an object's available degrees-of-freedom. Rather than estimating individual contact positions, we abstract out this calculation to an implicit representation, allowing the robot to either acquire, maintain, or release constraints on the object during the insertion process, by monitoring forces enacted on the end effector through time. Using a compliant robot, our method is desirable in that we are able to complete industry-relevant insertion tasks of tolerances <0.25mm without prior knowledge of the exact hole location or its orientation. We showcase our method on more generalized insertion tasks, such as commercially available non-cylindrical objects and open world plug tasks

Energy-Aware Ergodic Search: Continuous Exploration for Multi-Agent Systems with Battery Constraints

Continuous exploration without interruption is important in scenarios such as search and rescue and precision agriculture, where consistent presence is needed to detect events over large areas. Ergodic search already derives continuous trajectories in these scenarios so that a robot spends more time in areas with high information density. However, existing literature on ergodic search does not consider the robot's energy constraints, limiting how long a robot can explore. In fact, if the robots are battery-powered, it is physically not possible to continuously explore on a single battery charge. Our paper tackles this challenge, integrating ergodic search methods with energy-aware coverage. We trade off battery usage and coverage quality, maintaining uninterrupted exploration by at least one agent. Our approach derives an abstract battery model for future state-of-charge estimation and extends canonical ergodic search to ergodic search under battery constraints. Empirical data from simulations and real-world experiments demonstrate the effectiveness of our energy-aware ergodic search, which ensures continuous exploration and guarantees spatial coverage.Comment: 7 pages, 7 figures, ICRA'2

Estimation of Quasi-Stiffness of the Human Hip in the Stance Phase of Walking

Biomechanical data characterizing the quasi-stiffness of lower-limb joints during human locomotion is limited. Understanding joint stiffness is critical for evaluating gait function and designing devices such as prostheses and orthoses intended to emulate biological properties of human legs. The knee joint moment-angle relationship is approximately linear in the flexion and extension stages of stance, exhibiting nearly constant stiffnesses, known as the quasi-stiffnesses of each stage. Using a generalized inverse dynamics analysis approach, we identify the key independent variables needed to predict knee quasi-stiffness during walking, including gait speed, knee excursion, and subject height and weight. Then, based on the identified key variables, we used experimental walking data for 136 conditions (speeds of 0.75–2.63 m/s) across 14 subjects to obtain best fit linear regressions for a set of general models, which were further simplified for the optimal gait speed. We found R2 > 86% for the most general models of knee quasi-stiffnesses for the flexion and extension stages of stance. With only subject height and weight, we could predict knee quasi-stiffness for preferred walking speed with average error of 9% with only one outlier. These results provide a useful framework and foundation for selecting subject-specific stiffness for prosthetic and exoskeletal devices designed to emulate biological knee function during walking