Human-like Posture Research Articles

Human-Like Posture Correction for Seven-Degree-of-Freedom Robotic Arm

Abstract Owing to advancements in robotics, researchers have been focusing on integrating humanoid robots into actual environments. Most humanoid robots are equipped with seven-degree-of-freedom (DoF) arms that allow them to be flexible in different scenarios. The controller of a 7-DoF robotic arm must select one solution among the infinite sets of solutions for a given inverse kinematics problem. To date, no suitable approach has been developed for identifying appropriate human-like postures for a robotic arm with an offset wrist configuration. In this paper, we propose a novel algorithm that considers the movement of the human arm to consistently find a suitable human-like posture. First, a one-class support vector machine model is employed to classify human-like postures. Then, the algorithm uses the redundancy characteristic of a 7-DoF robotic arm with a linear regression model to enhance the search of human-like postures. Finally, the proposed algorithm is demonstrated in simulation, where it successfully optimized point-to-point trajectories by modifying only the endpoint posture.

Biological Plausibility of Arm Postures Influences the Controllability of Robotic Arm Teleoperation.

ObjectiveWe investigated how participants controlling a humanoid robotic arm’s 3D endpoint position by moving their own hand are influenced by the robot’s postures. We hypothesized that control would be facilitated (impeded) by biologically plausible (implausible) postures of the robot.BackgroundKinematic redundancy, whereby different arm postures achieve the same goal, is such that a robotic arm or prosthesis could theoretically be controlled with less signals than constitutive joints. However, congruency between a robot’s motion and our own is known to interfere with movement production. Hence, we expect the human-likeness of a robotic arm’s postures during endpoint teleoperation to influence controllability.MethodTwenty-two able-bodied participants performed a target-reaching task with a robotic arm whose endpoint’s 3D position was controlled by moving their own hand. They completed a two-condition experiment corresponding to the robot displaying either biologically plausible or implausible postures.ResultsUpon initial practice in the experiment’s first part, endpoint trajectories were faster and shorter when the robot displayed human-like postures. However, these effects did not persist in the second part, where performance with implausible postures appeared to have benefited from initial practice with plausible ones.ConclusionHumanoid robotic arm endpoint control is impaired by biologically implausible joint coordinations during initial familiarization but not afterwards, suggesting that the human-likeness of a robot’s postures is more critical for control in this initial period.ApplicationThese findings provide insight for the design of robotic arm teleoperation and prosthesis control schemes, in order to favor better familiarization and control from their users.

An Extended Passive Motion Paradigm for Human-Like Posture and Movement Planning in Redundant Manipulators.

A major challenge in robotics and computational neuroscience is relative to the posture/movement problem in presence of kinematic redundancy. We recently addressed this issue using a principled approach which, in conjunction with nonlinear inverse optimization, allowed capturing postural strategies such as Donders' law. In this work, after presenting this general model specifying it as an extension of the Passive Motion Paradigm, we show how, once fitted to capture experimental postural strategies, the model is actually able to also predict movements. More specifically, the passive motion paradigm embeds two main intrinsic components: joint damping and joint stiffness. In previous work we showed that joint stiffness is responsible for static postures and, in this sense, its parameters are regressed to fit to experimental postural strategies. Here, we show how joint damping, in particular its anisotropy, directly affects task-space movements. Rather than using damping parameters to fit a posteriori task-space motions, we make the a priori hypothesis that damping is proportional to stiffness. This remarkably allows a postural-fitted model to also capture dynamic performance such as curvature and hysteresis of task-space trajectories during wrist pointing tasks, confirming and extending previous findings in literature.

Robot motion synthesis using ground reaction forces pattern

Gait generation in its realization stage in majority of bipeds involves inverse dynamics model with the need of pre-determined joint trajectories and the zero moment point method for final postural stability adjustments. This requires generation of such joint trajectories, where the zero moment point criterion is fulfilled and the human-like posture is kept. Such task is complex and still misses the universal solution. Preserving natural (human-like) and stable body posture under acting disturbances is an issue too. High computational costs, problem with disturbances rejection and controller complexity are the major disadvantages associated with such approaches. This article presents a method for motion control with forward dynamics model and ground reaction forces as the reference values. The ground reaction forces measured during real human walking are utilized here. A MATLAB/Simulink framework is used for testing the proposed synthesis of bipedal locomotion. The ground reaction forces recorded during the walk with different footwear are applied as the references. The obtained motion patterns and postures are compared with those of the human. Obtained results were satisfactory and justified the proposed approach.

Kinematics Analysis of Serial-Parallel Hybrid Humanoid Robot in Reaching Movement

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260005/07.jpg"" width=""300"" />Serial-parallel hybrid robot</div> As the demand to the practical operation ability of humanoid robots improving, serial-parallel hybrid structure has started to be used in the research of humanoid robot. However, analytical solutions of the forward and inverse kinematics are hard to obtain due to the redundancy of humanoid robot and the complex topology of hybrid structure. Besides, humanoid robots should have the capability to complete complicated operation in the low structured task workspace. So, it should have not only the humanoid shape but also the behavior that adapts to the direct interaction with people. In this work, a novel 4-DOF hybrid humanoid robot was taken as an example, the forward kinematics equation was derived, the theory of screws and lie group and lie algebra were applied to calculate the end velocity. A numerical calculation method based on neurophysiology sensorimotor transformation model and fuzzy logic compensator was proposed to solve the inverse kinematics in reaching movement. The proposed strategy can make the robot execute reaching movements with human-like posture. Simulation and test results validate the effectiveness respectively. </span>