Kinematic Pose Research Articles

A magnetically actuated soft robot and its motion regulation

Inspired by molluscs, researchers have developed soft robots with greater freedom of movement and more adaptable to unstructured environments. Herein, a multi-locomotion soft robot based on magnetic composites is proposed. The space variable magnetic field impels the robot to generate a series of time-varying shapes, in order to accomplish all sorts of necessary motion gait. By integrating experimental exploration, theoretical research and finite element analysis, the pose kinematics of the robot are deeply analyzed, yielding an accurate description of its motion characteristics and fundamental laws. On this basis, control strategies are formulated to achieve customized crawling maneuvers and path planning for the robot in response to varying tasks. It is hoped that this research has profound significance for the improvement of traditional robots and the promotion of the development of intelligent devices.

A Novel Reconfigurable 3-DOF Parallel Kinematics Machine

Abstract This paper proposes a novel, reconfigurable parallel kinematics machine with three degrees of freedom that can be used for various three-axis manipulation tasks, including machining. By locking some joints, the proposed parallel kinematics machine (PKM) can be transformed into four topologies with eight configurations to attain certain kinematic properties while keeping the number of its degrees of freedom unchanged. Either the proximal or intermediate prismatic joints of the reconfigurable PKM can be actuated. Some of the configurations are orthogonal configurations having a large rectangular cuboid workspace, and some other configurations are non-orthogonal configurations which provide the capability to perform a machining task to a large workpiece in various positions with respect to the machine. Accordingly, the proposed machine can be transformed from an orthogonal machine to a non-orthogonal machine with the advantages of each. The mobility of the various topologies of the reconfigurable PKM is rigorously analyzed using the screw theory. The workspace is analyzed using a graphical approach and verified by a computational approach. The pose kinematics shows that the various topologies have unified kinematics. The differential kinematics shows that the singularities in the various configurations occur at the workspace boundary. Similarly, the stiffness analysis shows that the low-stiffness postures occur around the workspace boundary. Accordingly, a used workspace far from the workspace boundary easily avoids the singularities and the low stiffness.

A Reconfigurable Parallel Robot for On-Structure Machining of Large Structures

This paper presents a novel walking hybrid-kinematics robot that can be reconfigured to have three, five, and six degrees of freedom (DOFs) for adsorption machining of large structures. A symmetric 3PRPR or 3PRRR parallel mechanism with three translational (3T) DOFs is used to perform three-axis machining tasks. Three attachment pads connected to passive spherical joints are used to attach the robot to the surface of a large structure. Two or three rotational degrees of freedom can be added to the robot to adapt to a large structure’s irregular surface geometry and perform five- or six-axis machining tasks. This is achieved through modular reassembly or joint locking that reconfigures the robot from a three-DOF robot to a five- or six-DOF robot. A serial module providing two rotational DOFs can be added to the 3T parallel mechanism to provide five DOFs. A parallel module, namely 3SPR or 3SU mechanism, can be added to the 3T parallel mechanism to provide six DOFs. The mobility, pose kinematics, differential kinematics, singularities, and workspace of the 3SPR and 3SU parallel mechanisms alone and combined with the 3T mechanism are discussed in this paper. It is shown that the singularities of the mechanism can be easily avoided by making the moving platform of the 3SPR or 3SU mechanism smaller than the base, limiting the range of some joints, and having an appropriate length of the links. Furthermore, a method to optimize the workspace of the mechanism was also discussed.

Comparing the performance of Bayesian and least-squares approaches for inverse kinematics problems

Bayesian inference has recently been identified as an approach for estimating a subjects’ pose from noisy marker position data. Previous research suggests that Bayesian inference markedly reduces error for inverse kinematic problems relative to traditional least-squares approaches with estimators having reduced variance despite both least-squares and Bayesian estimators being unbiased. This result is surprising as Bayesian estimators are typically similar to least-squares approaches unless highly informative prior distributions are used. As a result the purpose of this work was to examine the sensitivity of Bayesian inverse kinematics solutions to the prior distribution. Our results highlight that Bayesian solutions to inverse kinematics are sensitive to the choice of prior and that the previously reported superior performance of Bayesian inference is likely due to an overly informative prior distribution which unrealistically uses knowledge of the true kinematic pose. When more realistic, ‘weakly-informative’ priors, which do not use the known kinematic pose are used then any improvements in estimator accuracy are minimal when compared to the traditional least squares approach. However, with appropriate priors, Bayesian inference can propagate uncertainties related to marker position to uncertainty in joint angles, a valuable contribution for kinematic analyses. When using Bayesian methods, we recommend researchers use weakly-informative priors and conduct a sensitivity analysis to highlight the effects of prior choice on analysis outcomes.

Adaptive nonlinear relative motion control of quadrotors in autonomous shipboard landings

The relative motion control for the unmanned quadrotors autonomous shipboard landings is investigated in this study. The shipboard landing missions are divided into two phases including the position approaching phase and the vertical landing phase. Relative pose kinematics and dynamics are modeled in the quadrotor’s body-fixed frame, where the kinematic couplings resulted from the difference between ship’s centre of mass and desired landing site and the unknown external disturbances of two vehicles are considered in the modeling and control design. In the position approaching phase, because of the under-actuated property of quadrotors, the adaptive backstepping technique is combined with an auxiliary system and a command filter to develop the guidance and control laws. Subsequently, the relative altitude-attitude controller is designed for the vertical landing phase. Stability analysis shows that the position approaching errors in the first phase and the landing errors in the second phase ultimately converge to small neighborhoods of zero, and numerical simulation validates the effectiveness of the proposed strategy.

Pose Observation for Second Order Pose Kinematics

This paper proposes an equivariant observer for second order pose estimation of a rigid body. The observer exploits the second order kinematic model and its symmetry group. The observer uses conventional sensors and simple computations that allow it to be run on resource-constrained devices. The observer design is based on the lifted kinematics and we prove its asymptotic convergence property. The performance of the observer is demonstrated in simulation.

Fast Blended Transformations for Partial Shape Registration

Automatic estimation of skinning transformations is a popular way to deform a single reference shape into a new pose by providing a small number of control parameters. We generalize this approach by efficiently enabling the use of multiple exemplar shapes. Using a small set of representative natural poses, we propose to express an unseen appearance by a low-dimensional linear subspace, specified by a redundant dictionary of weighted vertex positions. Minimizing a nonlinear functional that regulates the example manifold, the suggested approach supports local-rigid deformations of articulated objects, as well as nearly isometric embeddings of smooth shapes. A real-time nonrigid deformation system is demonstrated, and a shape completion and partial registration framework is introduced. These applications can recover a target pose and implicit inverse kinematics from a small number of examples and just a few vertex positions. The resulting reconstruction is more accurate compared to alternative reduced deformable models.

Design and kinematic optimization of a novel underactuated robotic hand exoskeleton

This study presents the design and the kinematic optimization of a novel, underactuated, linkage-based robotic hand exoskeleton to assist users performing grasping tasks. The device has been designed to apply only normal forces to the finger phalanges during flexion/extension of the fingers, while providing automatic adaptability for different finger sizes. Thus, the easiness of the attachment to the user’s fingers and better comfort have been ensured. The analyses of the device kinematic pose, statics and stability of grasp have been performed. These analyses have been used to optimize the link lengths of the mechanism, ensuring that a reasonable range of motion is satisfied while maximizing the force transmission on the finger joints. Finally, the usability of a prototype with multiple fingers has been tested during grasping tasks with different objects.

Accuracy assessment and kinematic calibration of the robotic endoscopic microsurgical system.

This paper explores the general stereotactic accuracy of the Robotic Endoscopic Microsurgical System (REMS) by calibrating with a standard optical tracking system. Based on a simple yet effective test protocol, the proposed calibration method combines hand-eye calibration with Bernstein polynomials to improve our kinematic pose accuracy.

Kinematics Model and Simulation for Motor of Four-link Electric Chair

The mechanical model of a four-link electric chair is studied and corresponding simulation experiment on it is conducted through research methods of the robot kinematics and dynamics. After studying the D-H matrix form of the planar motion mechanism,the kinematics model of the chair is established by D-H parameters method,and Matlab is used to achieve a rapid simulation of the chair's kinematic pose. The motor-selection problem of the chair is solved. Through the study of ergonomics with body-mass-distribution model,the electric chair's dynamics model is established and the calculation method of motor selection problem is achieved. Finally compared the calculation results with simulation results in Solidworks motion,it seems that mechanical model established can well predict motor torque changes in the chair design.

Gait recognition using Pose Kinematics and Pose Energy Image

Many of the existing gait recognition approaches represent a gait cycle using a single 2D image called Gait Energy Image (GEI) or its variants. Since these methods suffer from lack of dynamic information, we model a gait cycle using a chain of key poses and extract a novel feature called Pose Energy Image (PEI). PEI is the average image of all the silhouettes in a key pose state of a gait cycle. By increasing the resolution of gait representation, more detailed dynamic information can be captured. However, processing speed and space requirement are higher for PEI than the conventional GEI methods. To overcome this shortcoming, another novel feature named as Pose Kinematics is introduced, which represents the percentage of time spent in each key pose state over a gait cycle. Although the Pose Kinematics based method is fast, its accuracy is not very high. A hierarchical method for combining these two features is, therefore, proposed. At first, Pose Kinematics is applied to select a set of most probable classes. Then, PEI is used on these selected classes to get the final classification. Experimental results on CMU's Mobo and USF's HumanID data set show that the proposed approach outperforms existing approaches.

Tracking People on a Torus

We present a framework for monocular 3D kinematic pose tracking and viewpoint estimation of periodic and quasi-periodic human motions from an uncalibrated camera. The approach we introduce here is based on learning both the visual observation manifold and the kinematic manifold of the motion using a joint representation. We show that the visual manifold of the observed shape of a human performing a periodic motion, observed from different viewpoints, is topologically equivalent to a torus manifold. The approach we introduce here is based on the supervised learning of both the visual and kinematic manifolds. Instead of learning an embedding of the manifold, we learn the geometric deformation between an ideal manifold (conceptual equivalent topological structure) and a twisted version of the manifold (the data). Experimental results show accurate estimation of the 3D body posture and the viewpoint from a single uncalibrated camera.

Animating responsive characters with dynamic constraints in near-unactuated coordinates

This paper presents a technique to enhance a kinematically controlled virtual character with a generic class of dynamic responses to small perturbations. Given an input motion sequence, our technique can synthesize reactive motion to arbitrary external forces with a specific style customized to the input motion. Our method re-parameterizes the motion degrees of freedom based on joint actuations in the input motion. By only enforcing the equations of motion in the less actuated coordinates, our approach can create physically responsive motion based on kinematic pose control without explicitly computing the joint actuations. We demonstrate the simplicity and robustness of our technique by showing a variety of examples generated with the same set of parameters. Our formulation focuses on the type of perturbations that significantly disrupt the upper body poses and dynamics, but have limited effect on the whole-body balance state.

INTERACTIVE HUMAN POSE AND ACTION RECOGNITION USING DYNAMICAL MOTION PRIMITIVES

There is currently a division between real-world human performance and the decision making of socially interactive robots. This circumstance is partially due to the difficulty in estimating human cues, such as pose and gesture, from robot sensing. Towards bridging this division, we present a method for kinematic pose estimation and action recognition from monocular robot vision through the use of dynamical human motion vocabularies. Our notion of a motion vocabulary is comprised of movement primitives that structure a human's action space for decision making and predict human movement dynamics. Through prediction, such primitives can be used to both generate motor commands for specific actions and perceive humans performing those actions. In this paper, we focus specifically on the perception of human pose and performed actions using a known vocabulary of primitives. Given image observations over time, each primitive infers pose independently using its expected dynamics in the context of a particle filter. Pose estimates from a set of primitives inferencing in parallel are arbitrated to estimate the action being performed. The efficacy of our approach is demonstrated through interactive-time pose and action recognition over extended motion trials. Results evidence our approach requires small numbers of particles for tracking, is robust to unsegmented multi-action movement, movement speed, camera viewpoint and is able to recover from occlusions.

Omni-Wrist III - A new generation of pointing devices. I. Laser beam steering devices - mathematical modeling

Omni-Wrist III is a new sensor mount developed with U.S. Air Force funding that emulates the kinematics of a human wrist. Driven by two linear motors and computer controlled, it is capable of a full 180/spl deg/ hemisphere of pitch/yaw motion. A comprehensive laboratory testing of one of the few existing devices of this type, installed in the Laser Communications Research Laboratory at Binghamton University, has resulted in the establishment of a complete mathematical model relating pitch/yaw coordinates of the sensor mount to the motor encoder signals. This paper presents the development of the model that incorporates inverse and forward pose kinematics solutions as well as the dynamics of the novel gimbal-like pointing system.

3D Cable‐Based Cartesian Metrology System

AbstractA novel cable‐based metrology system is presented wherein six cables are connected in parallel from ground‐mounted string pots to the moving object or tool of interest. Cartesian pose can be determined for feedback control and other purposes by reading the lengths of the six cables via the string pots and using closed‐form forward pose kinematics. This article focuses on a sculpting metrology tool, assisting a human artist in generating a piece from a computer model, but applications exist in manufacturing, rapid prototyping, robotics, and automated construction. We present experimental data to demonstrate the operation of our system, we study the absolute accuracy and also measurement resolution, and we discuss various error sources. The proposed real‐time cable‐based metrology system is less complex and more economical than existing commercial Cartesian metrology technologies. © 2004 Wiley Periodicals, Inc.

Kinematic Calibration for Redundantly Actuated Parallel Mechanisms

We present a new kinematic calibration algorithm for redundantly actuated parallel mechanisms, and illustrate the algorithm with a case study of a planar seven-element 2-degree-of-freedom (DOF) mechanism with three actuators. To calibrate a nonredundantly actuated parallel mechanism, one can find actual kinematic parameters by means of geometrical constraint of the mechanism’s kinematic structure and measurement values. However, the calibration algorithm for a nonredundant case does not apply for a redundantly actuated parallel mechanism, because the angle error of the actuating joint varies with position and the geometrical constraint fails to be consistent. Such change of joint angle error comes from constraint torque variation with each kinematic pose (meaning position and orientation). To calibrate a redundant parallel mechanism, one therefore has to consider constraint torque equilibrium and the relationship of constraint torque to torsional deflection, in addition to geometric constraint. In this paper, we develop the calibration algorithm for a redundantly actuated parallel mechanism using these three relationships, and formulate cost functions for an optimization algorithm. As a case study, we executed the calibration of a 2-DOF parallel mechanism using the developed algorithm. Coordinate values of tool plate were measured using a laser ball bar and the actual kinematic parameters were identified with a new cost function of the optimization algorithm. Experimental results showed that the accuracy of the tool plate improved by 82% after kinematic calibration in a redundant actuation case.

Manipulability of a planar wire driven haptic device

This paper presents a planar 4 wire driven 3-DOF mechanism. For a planar haptic interface, this device could provide planar forces and moment feedback to the human operator. The particular end-effector geometric configuration overcomes manipulability problems arising from other recent planar wire haptic interfaces [R.L. Williams II, Int. J. Virtual Reality 3 (3) (1998) 13]. Moreover, an explicit forward kinematic pose solution is obtained by introducing a modified wire configuration. Complete kinematic and manipulability analyses are presented.

3-d.o.f. Wire Driven Planar Haptic Interface

A 4-wire driven 3-d.o.f. planar haptic device, called the Feriba-3, is described. The particular geometric configuration of the end-effector ensures a closed form kinematic pose solution and good manipulability. Moreover, the structural arrangement adopted makes the Feriba-3 a well-performing haptic device, whose major features are low inertia, low friction, and full dexterity in a large workspace. The manipulability analysis has been performed by introducing a complete set of manipulability indices.