Weighted hierarchical quadratic programming: assigning individual joint weights for each task priority

This paper proposes a novel method that computes the optimal solution of the weighted hierarchical optimization problem for both equality and inequality tasks. The method is developed to resolve the redundancy of robots with a large number of Degrees of Freedom (DoFs), such as a mobile manipulator or a humanoid, so that they can execute multiple tasks with differently weighted joint motion for each priority level. The proposed method incorporates the weighting matrix into the first-order optimality condition of the optimization problem and leverages an active-set method to handle equality and inequality constraints. In addition, it is computationally efficient because the solution is calculated in a weighted joint space with symmetric null-space projection matrices for propagating recursively to a low priority task. Consequently, robots that utilize the proposed method effectively show whole-body motions handling prioritized tasks with differently weighted joint spaces. The effectiveness of the proposed method was validated through experiments with a nonholonomic mobile manipulator as well as a humanoid.

     

Implementation and stability analysis of prioritized whole-body compliant controllers on a wheeled humanoid robot in uneven terrains

In this work, we implement the floating base prioritized whole-body compliant control framework described in Sentis et al. (IEEE Transactions on Robotics 26(3):483–501, 2010) on a wheeled humanoid robot maneuvering in sloped terrains. We then test it for a variety of compliant whole-body behaviors including balance and kinesthetic mobility on irregular terrain, and Cartesian hand position tracking using the co-actuated (i.e. two joints are simultaneously actuated with one motor) robot’s upper body. The implementation serves as a hardware proof for a variety of whole-body control concepts that had previously been developed and tested in simulation. First, behaviors of two and three priority tasks are implemented and successfully executed on the humanoid hardware. In particular, first and second priority tasks are linearized in the task space through model feedback and then controlled through task accelerations. Postures, on the other hand, are shown to be asymptotically stable when using prioritized whole-body control structures and then successfully tested in the real hardware. To cope with irregular terrains, the base is modeled as a six degree of freedom floating system and the wheels are characterized through contact and rolling constraints. Finally, center of mass balance capabilities using whole-body compliant control and kinesthetic mobility are implemented and tested in the humanoid hardware to climb terrains with various slopes.     

表征空间中的机器人分层运动规划

由于对机器人的任务要求日趋复杂和多变,如何使机器人具备灵活的配置和运动规划能力,以适应复杂任务的需求,成为了目前运动规划领域所研究的核心问题.传统的基于任务空间和配置空间的建模方法虽然在机器人运动规划领域得到了非常广泛的应用,但在用于解决复杂规划任务时无法对不可行任务进行进一步地处理.本文在表征空间模型的基础上,提出了一种分层的运动规划算法,一方面借助于表征空间维度的扩展,使对运动规划任务的描述更为灵活;另一方面通过任务层与运动层的循环交互,使生成的路径满足更高层次和更丰富的任务要求.在仿人机器人和多机器人系统上的应用结果表明了本文所提算法的有效性.     

Adaptive Control For Robotic Manipulators Executing Multilateral Constrained Task

This paper presents a model‐based adaptive control in task coordinates for robotic manipulators executing multilateral constrained tasks The controller works based on the concept of orthogonality between force and motion in the subspaces derived from the constraints. The control gains are independently adjustable in each subspace. The friction force, depending on the contact force, is compensated adaptively. Asymptotic convergence for both force and motion tracking errors is guaranteed by the Lyapunov‐Like Lemma. Experimental results obtained using a 3 D.O.F. robot are given.     

Stabilization of robot motion and contact force interaction for third-order motor dynamics

An approach to the synthesis of control laws stabilizing motion and force in contact tasks, based on the exponential stability of the closed-loop control system, is described. When using the synthesized control laws, simultaneous stabilization of both motion and force is achieved with a preset quality of the transient responses. The task is solved in a most general form, taking into account the constraints on robot control, its position and the force of interaction of the robot and the environment, and the external perturbations and inaccuracies of the measuring sensors, when the environment dynamics is being described by nonlinear second-order differential equation, and the robot dynamics includes the third-order equations of the robot actuators dynamics.     

Experimental Implementation of Impedance Based Control Schemes for Assembly Task

Compliant manipulation tasks require the robot to follow a motion trajectory and to exert a force profile while making compliant contact with a dynamic environment. For this purpose, a generalized impedance in the task space is introduced such that the desired motion and the desired interaction force can be commanded and controlled simultaneously. Several control schemes which place different emphases on motion control or force control can be derived from the generalized impedance. The impedance-based control schemes are implemented and the performance evaluated on a common test-bed which involves the insertion of a printed circuit board into an edge connector socket. Experimental results demonstrate the superior motion and force tracking ability of the generalized impedance control method. Furthermore, safe task execution can be achieved in the presence of abnormal operating situation.     

Adaptive robust control and admittance control for contact-driven robotic surface conditioning

This work presents a hybrid position/force control of robots for surface contact conditioning tasks such as polishing, profiling, deburring, etc. The robot force control is designed using sliding mode ideas to benefit from robustness. On the one hand, a set of equality constraints are defined to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. On the other hand, inequality constraints are defined to adapt the tool position to unmodeled features present in the surface, e.g., a protruding window frame. Conventional and non-conventional sliding mode controls are used to fulfill the equality and inequality constraints, respectively. Furthermore, in order to deal with sudden changes of the material stiffness, which are forwarded to the robot tool and can produce instability and bad performance, adaptive switching gain laws are considered not only for the conventional sliding mode control but also for the non-conventional sliding mode control. A lower priority tracking controller is also defined to follow the desired reference trajectory on the target surface. Moreover, the classical admittance control typically used in force control tasks is adapted for the proposed surface contact application in order to experimentally compare the performance of both control approaches. The effectiveness of the proposed method is substantiated by experimental results using a redundant 7R manipulator, whereas its advantages over the classical admittance control approach are experimentally shown.     

云环境下基于任务分类和LPM优化模型的调度算法

针对用户任务预算不足或期望完成时间较短,云服务方无法保障任务全部完成,提出基于任务分类和线性规划优化模型调度策略,使任务完成数最大化,同时考虑任务重要性。算法根据任务长短及重要性进行分类,然后建立任务计算资源关系矩阵及3个相关约束条件,以任务完成数最大化为目标函数,搭建线性规划模型,并给出算法实现。模拟实验表明,在同样的用户任务预算和期望完成时间条件下,该算法任务完成数最大值明显高于经典算法。     

Backward Ladder Climbing Locomotion of Humanoid Robot with Gain Overriding Method on Position Control

We studied ladder climbing locomotion with the humanoid robot, DRC‐HUBO, under the constraints suggested by DARPA. Considering the hardware constraints of the robot platform, we planned for the robot to climb backward with four limbs moving separately. Task‐priority whole‐body inverse kinematics was used to generate and track the motion while maintaining COM inside the support polygon. As ladder climbing is a multicontact motion that generates interaction and internal forces, we resolved these issues using a gain overriding method applied to the position control of the motor controllers. This paper also provides various vision methods and posture modification strategies for the restricted conditions of the challenge. We ultimately verified our work in the DRC trials by getting a full score on the ladder task.     

Towards cooperation of heterogeneous,autonomous robots: A case study of humanoid and wheeled robots

In this paper a case study of the cooperation of a strongly heterogeneous autonomous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some redundant abilities is presented. By combining strongly heterogeneous robots the diversity of achievable tasks increases as the variety of sensing and motion abilities of the robot system is extended, compared to a usually considered team of homogeneous robots. A number of methodologies and technologies required in order to achieve the long-term goal of cooperation of heterogeneous autonomous robots are discussed, including modeling tasks and robot abilities, task assignment and redistribution, robot behavior modeling and programming, robot middleware and robot simulation. Example solutions and their application to the cooperation of autonomous wheeled and humanoid robots are presented in this case study. The scenario describes a tightly coupled cooperative task, where the humanoid robot and the wheeled robot track a moving ball, which is to be approached and kicked by the humanoid robot into a goal. The task can be fulfilled successfully by combining the abilities of both robots.     

Hybrid Force and Vision-Based Contour Following of Planar Robots

Manipulators interacted with uncalibrated environments have limited dexterity due to constraints imposed by unknown environments. However, to perform science or industrial operations, it is necessary to be able to position and orient these manipulators on targets in order to accomplish required control tasks. This article describes how one might enhance manipulator dexterity for planar contour following tasks using hybrid force and vision-based control. The proposed control approach can guarantee task precision employing only a single-axis force sensor and an imprecisely calibrated CCD camera whose optical axis is perpendicular to the planar workspace. The goal of the autonomous task is to drive an instrument mounted on the end-effector of a planar robotic manipulator to follow a visually determined planar contour and continue tracking the contour in desired pose, contact force, and speed, all demanding time-varying, with precision. The proposed control architecture is suitable for applications that require simultaneous force and pose control in unknown environments. Our approach is successfully validated in a real task environment by performing experiments with an industrial robotic manipulator.     

Online generation and control of quasi-static multi-contact motion by PWT Jacobian matrix with contact wrench estimation and joint load reduction*

In this paper, we propose a generic method of online motion generation and control that realizes quasi-static multi-contact motion for real position-controlled humanoids. The proposed system calculates command joint angle online by prioritized inverse kinematics that realizes the target contact states and the target position/orientation of interaction end-effectors feasibly. In order to enable control of contact wrench and joint torque with position-controlled robots, Jacobian matrixes (PWT Jacobian matrix) focusing on relationships between command joint angle and actual joint position, contact wrench, and joint torque are introduced. In addition, contact wrench is estimated at the body parts where force sensors are not mounted to enable contacts there, and joint load reduction based on the motor temperature is taken into account to enable long-term motions with real humanoids. The proposed method was verified by a real life-size position-controlled humanoid HRP2-JSKNTS, and various multi-contact motions such as desk climbing using the right knee and both arms were realized.     

Momentum control with hierarchical inverse dynamics on a torque-controlled humanoid

Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.     

Whole-body collision avoidance control design using quadratic programming with strict and soft task priorities

Despite safe mechanical design is necessary for the collaborative robots, we can not underestimate the importance of active safety due to a multi-objective control design. Active safety not only complements the mechanical compliance but also enables classical industrial robots the ability to fulfill additional task-space objectives. Using the gradient of the collision avoidance task as hard constraints of a quadratic programming (QP) controller, we assign strict priority to avoid collisions and specify other QP controller objectives with soft task priorities. Through experiments performed on a dual-arm robot, we show that the proposed solution is able to generate safe robot motion that fulfills the task specifications while keeping the feasibility of the underlying quadratic optimization problem.     

Balancing of humanoid robot using contact force/moment control by task-oriented whole body control framework

Balancing control of humanoid robots is of great importance since it is a necessary functionality not only for maintaining a certain position without falling, but also for walking and running. For position controlled robots, the for-ce/torque sensors at each foot are utilized to measure the contact forces and moments, and these values are used to compute the joint angles to be commanded for balancing. The proposed approach in this paper is to maintain balance of torque-controlled robots by controlling contact force and moment using whole-body control framework with hierarchical structure. The control of contact force and moment is achieved by exploiting the full dynamics of the robot and the null-space motion in this control framework. This control approach enables compliant balancing behavior. In addition, in the case of double support phase, required contact force and moment are controlled using the redundancy in the contact force and moment space. These algorithms are implemented on a humanoid legged robot and the experimental results demonstrate the effectiveness of them.     

Bilateral remote teaching and autonomous task execution with task progress feedback

This paper describes an approach to estimating the progress in a task executed by a humanoid robot and to synthesizing motion based on the current progress so that the robot can achieve the task. The robot observes a human performing whole body motion for a specific task, and encodes these motions into a hidden Markov model (HMM). The current observation is compared with the motion generated by the HMM, and the task progress can be estimated during the robot performing the motion. The robot subsequently uses the estimate of the task progress to generate a motion appropriate to the current situation with the feedback rule. We constructed a bilateral remote control system with humanoid robot HRP-4 and haptic device Novint Falcon, and we made the humanoid robot push a button. Ten trial motions of pushing a button were recorded for the training data. We tested our proposed approach on the autonomous execution of the pushing motion by the humanoid robot, and confirmed the effectiveness of our task progress feedback method.     

基于螺旋模型的仿人机器人步态参数优化算法

步行运动是仿人机器人运动控制的关键环节之一.为了实现快速、稳定的步态,在协方差矩阵自适应进化策略(CMA-ES)的基础上,文中提出仿人机器人螺旋模型算法.在步行优化过程中,将优化任务先划分为3个子任务,按照优化目标分别挑选参数加入相应优化组,同时构建CMA-ES优化器.根据不同的学习目标设计每个CMA-ES优化器,在前一优化组优化结果基础上结合新的需求进行螺旋迭代优化,最终达到既定的学习目标,获得最佳参数值.文中算法应用在HfutEngine仿真3D球队中,机器人的相关步态测试数据显示算法效果较佳.     

Humanoid Robotic System with and without Elasticity Elements Walking on an Immobile/Mobile Platform

This work is concerned with the modeling and analysis of a complex humanoid robotic system walking on an immobile/mobile platform. For this purpose, a software package was synthesized which allows one to select configuration of both the humanoid and the platform. Each joint of the biped and platform can be defined by the user via the motor state (active or locked) and gear type (rigid or elastic). The user can also form very diverse configurations of the humanoid and platform. The software package forms a mathematical model. By selecting system’s parameters the simulation allows user to analyze dynamic behavior of the biped of selected configuration, walking on either an immobile or mobile platform of selected configuration. In the moment when the biped steps on the platform, the latter, by its dynamics, acts on the biped dynamics, and the biped on the other hand, by its characteristics, influences dynamics of the platform motion. These two complex contacting systems form a more complex system, whose mathematical model has to encompass all the elements of coupling between the humanoid joints and platform joints. The phenomenon of coupling is analyzed first on a humanoid robotic system with all rigid elements, which is in contact with the platform mechanism having also all rigid elements. It has been shown that coupling is more influenced when elasticity elements are included into the configuration. Insufficient knowledge of coupling characteristics may present a serious disturbance to the system in the robotic task realization. The deviation of the ZMP (Zero-Moment Point) from the reference trajectory is presented, which implies the need for the synthesis of new control structures for stabilizing biped motion on the immobile/mobile platform. The reference trajectory may be defined in very different ways and from several aspects. Reference trajectory of each joint can be defined so to encompass or not encompass elastic deformations. The control structure for the biped walking on the platform should be defined so that it satisfies the requirement for the ZMP to be within the given boundaries in every sampling instant, which guarantees dynamic balance of the locomotion mechanism in the real regime. The control is defined as CR (Centralized Reference control, calculated from the reference state), plus LO (control via local feedbacks of motor motion with respect to position and velocity). In the case of the biped motion on a mobile platform CR control is defined separately under the real conditions of unknown characteristics of coupling between the two complex systems, as well as unknown elasticity properties. The analysis of simulation results of the humanoid robot motion on a mobile platform gives evidence for all the complexity of this system and shows how much system parameters (choice of trajectory, configuration, geometry, elasticity characteristics, motor, etc.) influence stabilization of its humanoid motion.