Performance Analysis of Sawing Based on Impulse Measure and Geometry—Dublahal Arm Approach

Some of manufacturing tasks, such as sawing, often require continuous impulsive motion. In the case of sawing, such impulsive motions can be observed between the teeth of the saw and the object. The amount of the external impulse exerted on the object has been treated as an important control parameter. At the same time, the internal impulses experienced at the joints should be taken into account to avoid serious damage or injury at the joints of robot. The purpose of this paper is to improve the efficacy of sawing by using dual arms. For this, we suggest an external impulse model, and introduce a new concept of effective mass that accounts for the hardness of the object to corroborate the effectiveness of the proposed chip model employed in the derivation of the external impulse model. Closed-form internal impulse models are also proposed for both single and dual arms. Based on these models, the paper proposes a new measure for internal impulse. A normalized impulse ellipsoid reflecting the velocity direction is employed to visualize the impact geometry. Finally, we identify the optimal sawing region, wherein there is a maximum amount of external impulse and a minimal amount of the internal impulse. Simulation and experimentation demonstrate that the dual arm exhibits a better sawing performance than a single arm, in terms of external and internal impulses.     

Compact laparoscopic assistant robot using a bending mechanism

This paper presents the development of a compact laparoscopic assistant robot. The robot was designed to increase convenience and reduce possible interference with surgical staff by confining the majority of motions inside the abdomen. Its size was miniaturized as much as possible for convenient handling. A bending mechanism composed of several articulated joints was introduced to produce motions inside the abdomen. The proposed assistant robot can generate 3-DOF motion, including 2-DOF internal bending motion and 1-DOF external linear motion. Since the robot itself functions as a laparoscope, a small CCD camera module and a bundle of optical fibers were integrated as part of the system. For accurate control, mathematical modeling of the bending mechanism and a method of hysteresis compensation were introduced and implemented. For the control of the robot, a voice interface and a visual-servoing method were implemented. The performance of the developed system was tested through solo-surgery of in vivo porcine cholecystectomy. It was found that the views generated by the bending mechanism were sufficient throughout the surgery. Since the robot has functions comparable to the previously developed systems, while retaining its compactness, it is expected to be a useful device for human cholecystectomy.     

Whole-Body Motion Generation Integrating Operator's Intention and Robot's Autonomy in Controlling Humanoid Robots

This paper introduces a framework for whole-body motion generation integrating operator's control and robot's autonomous functions during online control of humanoid robots. Humanoid robots are biped machines that usually possess multiple degrees of freedom (DOF). The complexity of their structure and the difficulty in maintaining postural stability make the whole-body control of humanoid robots fundamentally different from fixed-base manipulators. Getting hints from human conscious and subconscious motion generations, the authors propose a method of generating whole-body motions that integrates the operator's command input and the robot's autonomous functions. Instead of giving commands to all the joints all the time, the operator selects only the necessary points of the humanoid robot's body for manipulation. This paper first explains the concept of the system and the framework for integrating operator's command and autonomous functions in whole-body motion generation. Using the framework, autonomous functions were constructed for maintaining postural stability constraint while satisfying the desired trajectory of operation points, including the feet, while interacting with the environment. Finally, this paper reports on the implementation of the proposed method to teleoperate two 30-DOF humanoid robots, HRP-1S and HRP-2, by using only two 3-DOF joysticks. Experiments teleoperating the two robots are reported to verify the effectiveness of the proposed method.     

A novel formulation for determining joint constraint loads during optimal dynamic motion of redundant manipulators in DH representation

The kinematic representations of general open-loop chains in many robotic applications are based on the Denavit–Hartenberg (DH) notation. However, when the DH representation is used for kinematic modeling, the relative joint constraints cannot be described explicitly using the common formulation methods. In this paper, we propose a new formulation of solving a system of differential-algebraic equations (DAEs) where the method of Lagrange multipliers is incorporated into the optimization problem for optimal motion planning of redundant manipulators. In particular, a set of fictitious joints is modeled to solve for the joint constraint forces and moments, as well as the optimal dynamic motion and the required actuator torques of redundant manipulators described in DH representation. The proposed method is formulated within the framework of our earlier study on the generation of load-effective optimal dynamic motions of redundant manipulators that guarantee successful execution of given tasks in which the Lagrangian dynamics for general external loads are incorporated. Some example tasks of a simple planar manipulator and a high-degree-of-freedom digital human model are illustrated, and the results show accurate calculation of joint constraint loads without altering the original planned motion. The proposed optimization formulation satisfies the equivalent DAEs.     

Creating and retargetting motion by the musculoskeletal human body model

Recently, optimization has been used in various ways to interpolate or retarget human body motions obtained by motion-capturing systems. However, in such cases, the inner structure of a human body has rarely been taken into account, and hence there have been difficulties in simulating physiological effects such as fatigue or injuries. In this paper, we propose a method to create/retarget human body motions using a musculoskeletal human body model. Using our method, it is possible to create dynamically and physiologically feasible motions. Since a muscle model based on Hill's model is included in our system, it is also possible to retarget the original motion by changing muscular parameters. For example, using the muscle fatigue model, a motion where a human body gradually gets tired can be simulated. By increasing the maximal force exertable by the muscles, or decreasing it to zero, training or displacement effects of muscles can also be simulated. Our method can be used for biomechanically correct inverse kinematics, interpolation of motions, and physiological retargetting of the human body motion.     

Motion Sickness Simulation Based on Sensorimotor Control

Sensorimotor control is an essential mechanism for human motions, from involuntary reflex actions to intentional motor skill learning, such as walking, jumping, and swimming. Humans perform various motions according to different task goals and physiological sensory perception; however, most existing computational approaches for motion simulation and generation rarely consider the effects of human perception. The assumption of perfect perception (i.e., no sensory errors) of existing approaches restricts the generated motion types and makes dynamical reactions less realistic. We propose a general framework for sensorimotor control, integrating a balance controller and a vestibular model, to generate perception‐aware motions. By exploiting simulated perception, more natural responses that are closer to human reactions can be generated. For example, motion sickness caused by the impairments in the function of the vestibular system induces postural instability and body sway. Our approach generates physically correct motions and reasonable reactions to external stimuli since the spatial orientation estimation by the vestibular system is essential to preserve balance. We evaluate our framework by demonstrating standing balance on a rotational platform with different angular speeds and duration. The generated motions show that either faster angular speeds or longer rotational duration cause more severe motion sickness. Our results demonstrate that sensorimotor control, integrating human perception and physically‐based control, offers considerable potential for providing more human‐like behaviors, especially for perceptual illusions of human beings, including visual, proprioceptive, and tactile sensations.     

Real‐time Locomotion Controller using an Inverted‐Pendulum‐based Abstract Model

In this paper, we propose a novel motion controller for the online generation of natural character locomotion that adapts to new situations such as changing user control or applying external forces. This controller continuously estimates the next footstep while walking and running, and automatically switches the stepping strategy based on situational changes. To develop the controller, we devise a new physical model called an inverted‐pendulum‐based abstract model (IPAM). The proposed abstract model represents high‐dimensional character motions, inheriting the naturalness of captured motions by estimating the appropriate footstep location, speed and switching time at every frame. The estimation is achieved by a deep learning based regressor that extracts important features in captured motions. To validate the proposed controller, we train the model using captured motions of a human stopping, walking, and running in a limited space. Then, the motion controller generates human‐like locomotion with continuously varying speeds, transitions between walking and running, and collision response strategies in a cluttered space in real time.     

欠驱动航天器相对运动的姿轨耦合控制

针对欠驱动的非对称航天器设计六自由度相对运动的姿轨耦合控制器.首先,给出用对偶四元数描述的六自由度相对运动模型;然后,基于矩阵广义逆和空控制向量提出广义的滑模控制器,以实现相对姿态欠驱动控制的渐近稳定;最后,考虑姿轨耦合特性,利用高斯伪谱法和非线性规划得到相对轨道运动能量最省的轨迹,进而利用滑模变结构控制实现对该轨迹的跟踪.仿真结果表明,所提出的方法是有效和可行的,而且较其他方法消耗的能量更少.     

一种基于传感器的人体上肢运动实时跟踪方法

实时跟踪人体运动是人机交互的重要研究课题,可以广泛应用于虚拟现实、虚拟人运动合成、聋人手语自动生成、计算机3D动画、机器人运动控制、远程人机交互等领域。文中介绍了一种基于传感器的人体上肢运动实时跟踪方法,给出了该方法的虚拟人模型、计算原理与校正方法,最后介绍了整个方法的实现以及在中国聋人手语自动合成中的应用。该方法具有使用传感器少,运动跟踪精度高、计算过程简单而且速度快等特点。     

A Muscle-based Feed-forward Controller of the Human Body

There is an increasing demand for human body motion data. Motion capture and physical animation have been used to generate such data. It is, however, apparent that such methods cannot automatically generate arbitrary human body motions. A human body is a redundant multi-linked body controlled by a number of muscles. For this reason, the muscles must work appropriately and cooperatively for controlling the whole body. It is well-known that the human body control system is composed of two parts: The open-loop feed-forward control system and the closed-loop feedback control system. Many researchers have investigated the characteristics of the latter by analyzing the response of a human body to various external perturbations. However, for the former, very few studies have been done. This paper proposes an open-loop feed-forward model of the lower extremities which includes postural control for accurate animation of a human body. Assumptions are made here that the feed-forward controller minimizes a certain objective value while keeping the balance of the body stable. The actual human motion data obtained using a motion capturing technique is compared with the trajectory calculated using our method for verification. The best criteria which is based on muscle dynamics is proposed. Using our method, dynamically correct human animation can be created by merely specifying a few key postures.     

Enriching a motion database by analogous combination of partial human motions

We have synthesized new human body motions from existing motion data, by dividing the body of an animated character into several parts, such as upper and lower body, and partitioning the motion of the character into corresponding partial motions. By combining different partial motions, we can generate new motion sequences. We select the most natural-looking combinations by analyzing the similarity of partial motions, using techniques such as motion segmentation, dimensionality reduction, and clustering. These new combinations can dramatically increase the size of a motion database, allowing more score in selecting motions to meet constraints, such as collision avoidance. We verify the naturalness and physical plausibility of the new motions using an SVM learning model and by analysis of static and dynamic balance.     

Optimal motion cueing for 5-DOF motion simulations via a 3-DOF motion simulator

This study presents a novel motion-cueing strategy, which is applied to a motion simulator with three rotational degrees of freedom (DOF) to perform the roll, pitch, yaw, surge, and sway motions by using an online optimization algorithm. The weighting functions are adaptively tuned in each step, and the optimal Euler angles are obtained analytically. This motion-cueing algorithm is efficient since it requires no recursive search on the optimal solution. Experiments demonstrating the validity of the 5-DOF motion simulation are also included.     

耦合型3自由度并联稳定平台机构及其运动特征

基于舰船摇荡运动的耦合特征,采用耦合型3-SRR/SRU 3自由度并联机构作为舰载稳定平台机构,实现了稳定平台三轴驱动、动平台五轴联动补偿的目标．运用螺旋理论分析了机构的自由度和运动特征, 并讨论了输入关节选取的合理性|采用坐标等效运动的方法,建立机构耦合运动约束方程,得到了位置解及工作空间．本文将耦合型3-SRR/SRU 3自由度并联机构用于舰载稳定平台五轴联动补偿,拓展了少自由度并联机构的应用领域．     

Optimal control of dual-mass system motion in a medium with a piecewise linear resistance

Linear motion of a mechanical system consisting of two bodies??a container and an inner body??is considered. The container is located in an external medium with resistance, and the inner body moves inside the container without the interaction with the external medium. Under certain conditions, the periodic motion of the inner body causes the system as a whole to move. The external medium acts on the container with a force that is proportional to its velocity with a resistance coefficient depending on the motion direction. Only the motions of the inner body with continuous relative velocity are studied. The optimal periodic motion of the inner body corresponding to the greatest period-averaged velocity of the system as a whole is constructed and analyzed.     

Dynamics of a three-module vibration-driven system with non-symmetric Coulomb’s dry friction

In the present paper, a three-module vibration-driven system moving on a rough horizontal plane is modeled to investigate the relation among the system’s steady-state motion, external Coulomb’s dry friction force and internal excitations. Each module of the system represents a vibration-driven system composed of a rigid body and a movable internal mass. Major attention is focused on the primary resonance situation that the excitation frequency is close to the first-order natural frequency of the system. In the case that the external friction is low, the internal excitation is weak and the stick–slip motion is negligible, both methods of averaging and modal superposition are employed to study the steady-state motion of the system. Through a set of algebraic equations, an approximate value of the system’s average steady-state velocity is obtained. Several numerical examples are calculated to verify the validity of the analytical results both qualitatively and quantitatively. It is seen that big quantitative errors will appear if stick–slip motions occur. Then, two mechanisms for the possible stick–slip motions are put forward, which explain the errors on the average steady-state velocity. Numerical simulations verify our analysis on the stick–slip effects and their mechanisms. Finally, to maximize the average steady-state velocity of the system, optimal control problem is studied. It is shown that, in addition to modifying the friction coefficients, the improvement of the system’s efficiency can be provided by changing the initial phase shifts among the three internal excitations.     

Toward memory-based human motion simulation: development and validation of a motion modification algorithm

Computer simulation of human motions helps test hypotheses on human motion planning and fosters timely and high-quality human-machine/environment interaction design. The current study introduces a novel simulation approach termed memory-based motion simulation (MBMS), and presents its key element "motion modification" (MoM) algorithm. The proposed approach implements a computational model inspired by the generalized motor program (GMP) theory. Operationally, when a novel motion scenario is submitted to the MBMS system, its motion database is searched to find relevant existing motions. The selected motions, referred to as "root motions", most likely do not meet exactly the novel motion scenario, and therefore, they need to be modified by the MoM algorithm. This algorithm derives a parametric representation of possible variants of a root motion in a GMP-like manner, and adjusts the parameter values such that the new modified motion satisfies the novel motion scenario, while retaining the root motion's overall angular movement pattern and inter-joint coordination. An evaluation of the prediction capability of the algorithm, using both seated upper body reaching and whole-body load-transfer motions, indicated that the algorithm can accurately predict various human motions with errors comparable to the inherent variability in human motions when repeated under identical task conditions.     

Robust Physics‐based Motion Retargeting with Realistic Body Shapes

Motion capture is often retargeted to new, and sometimes drastically different, characters. When the characters take on realistic human shapes, however, we become more sensitive to the motion looking right. This means adapting it to be consistent with the physical constraints imposed by different body shapes. We show how to take realistic 3D human shapes, approximate them using a simplified representation, and animate them so that they move realistically using physically‐based retargeting. We develop a novel spacetime optimization approach that learns and robustly adapts physical controllers to new bodies and constraints. The approach automatically adapts the motion of the mocap subject to the body shape of a target subject. This motion respects the physical properties of the new body and every body shape results in a different and appropriate movement. This makes it easy to create a varied set of motions from a single mocap sequence by simply varying the characters. In an interactive environment, successful retargeting requires adapting the motion to unexpected external forces. We achieve robustness to such forces using a novel LQR‐tree formulation. We show that the simulated motions look appropriate to each character's anatomy and their actions are robust to perturbations.     

Biomechanics of manual material handling through simulation: Computational aspects

Computerized human motion simulation allows generation of dynamic human motions on computers. Biomechanical stresses can be estimated using the motions generated on a computer without actually collecting joint coordinate data. A two-dimensional whole-body lifting simulation model is presented in this paper. The model assumes that humans perform lifting activities based on minimization of physical work, subject to various constraints. The simulation method contains three major computation units: trajectory formation unit, dynamics of motion unit, and nonlinear optimization unit. The trajectory formation unit generates smooth polynomials representing motion characteristics of human lifting. Kinematics and kinetics are calculated in the dynamics unit. Objective and constraint functions are evaluated in the optimization unit. Optimal motions are generated by minimizing the objective function, subject to the constraints. Computation methods of the three units and simulation results are presented.     

Wearable master device for spinal injured persons as a control device for motorized wheelchairs

This paper describes a wearable, master device for people with a spinal injury who can move their neck and shoulders but cannot move their legs and arms. A device that measures the movements of their neck or shoulder can help them to drive a wheelchair. The sensors of such a wearable master device must be lightweight, small, and easily attached to cloth. Therefore, optical fiber curvature sensors are used to measure the human body motion. For a previously developed wearable master device, two calibration and mapping methods with, the sensors are proposed to extract 2-DOF human shoulder motions. One is constructed with simple geometric equations. The other is constructed with a multilayered artificial neural network. The two methods are compared. Experimental results show that the wearable master device can be used effectively for a 2-DOF input device for handicapped persons. It was also shown that a subject can control a mobile robot with the wearable master device.