scholarly journals Implementing Torque Control with High-Ratio Gear Boxes and Without Joint-Torque Sensors

2016 ◽  
Vol 13 (01) ◽  
pp. 1550044 ◽  
Author(s):  
Andrea Del Prete ◽  
Nicolas Mansard ◽  
Oscar E. Ramos ◽  
Olivier Stasse ◽  
Francesco Nori
Keyword(s):  
Position Control ◽  
Humanoid Robots ◽  
High Ratio ◽  
Torque Control ◽  
Joint Torque ◽  
Whole Body ◽  
Original Position ◽  
Reference Trajectory ◽  
Software Interface ◽  
Position Controller

This paper presents a complete framework (estimation, identification and control) for the implementation of joint-torque control on the humanoid robot HRP-2. While torque control has already been implemented on a few humanoid robots, this is one of the first implementations of torque control on a robot that was originally built to be position controlled (iCub [F. Nori, S. Traversaro, J. Eljaik, F. Romano, A. Del Prete and D. Pucci, iCub whole-body control through force regulation on rigid non-coplanar contacts, Frontiers in Robotics and AI 2 (2015).] and Asimo [O. Khatib, P. Thaulad and J. Park, Torque-position transformer for task control of position controlled robots, 2008 IEEE Int. Conf. Robotics and Automation, May 2008, pp. 1729–1734.] being the first two, to the best of our knowledge). The challenge comes from both the hardware, which does not include joint-torque sensors and presents large friction due to the high-ratio gear boxes, and the software interface, which only accepts desired joint-angle commands (no motor current/voltage control). The contribution of the paper is to provide a complete methodology that is very likely to be reproduced as most robots are designed to provide only position control capabilities. Additionally, the method is validated by exhaustive experiments on one leg of the robot, including a comparison with the original position controller. We tested the torque controller in both motion control and cartesian force control. The torque control can track better a reference trajectory while using lower values for the feedback gains (up to 25%). Moreover, we verified the quality of the identified motor models by analyzing the contribution of the feedforward terms of our torque controller, which dominate the feedback terms.

scholarly journals Whole-Body Operational Space Control for Locomotion and Manipulation

2015 ◽  
Vol 137 (06) ◽  
pp. S2-S6
Author(s):  
Luis Sentis
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Humanoid Robots ◽  
Rigid Body Dynamics ◽  
Joint Torque ◽  
Whole Body ◽  
Operational Space ◽  
Body Dynamics ◽  
Service Oriented ◽  
High Level

This article discusses the various researches being undertaken to study and develop Whole-Body Operational Space Control (WBOSC). The WBOSC emerges as a capable framework for real-time unified control of motion and force of humanoid robots. It could theoretically outperform high-speed industrial manipulators while providing the grounds for new types of service-oriented applications that require contact, by exploiting the rigid body dynamics of systems. By relying on joint torque sensors, WBOSC opens up the potential to interact with the physical environment using any part of the robot’s body while regulating the effective mechanical impedances to safe values. With ControlIt!, the developers provide a strict and easy way to use the WBOSC API consisting of compound tasks which define the operational space, and constraint sets that define the contacts with the environment as well as dependent degrees of freedom. ControlIt! is easy to connect to high level planners.

A model-based PID-like motion control method for flexible-joint manipulator with harmonic drives

2021 ◽  
pp. 095440622110369
Author(s):  
Guocai Yang ◽  
Yechao Liu ◽  
Junhong Ji ◽  
Minghe Jin ◽  
Songhao Piao
Keyword(s):  
Position Control ◽  
Control Method ◽  
Joint Torque ◽  
Dynamics Model ◽  
Motion Error ◽  
Flexible Joint ◽  
Speed Range ◽  
Position Controller ◽  
Flexible Joint Manipulator ◽  
Better Than

A novel control method is proposed to achieve high trajectory tracking precision, for flexible-joint manipulators. The method consists of three major parts: joint torque generator, joint torque tracker and motor position controller. The expected torque is generated by a PID controller based on the manipulator’s rigid dynamics model. In the torque tracker, motor position is corrected in both feedback and feedforward ways. Finally, the motor position controller is responsible to track the corrected motor trajectory to achieve the torque and position control. To suppress nonlinear friction, a disturbance observer is also implemented. The method is verified with a seven-DOFs manipulator. Simulation and experimental results show that, the proposed method is efficient and practical to suppress vibration caused by flexible transmission and disturbance due to friction. As result, high positioning accuracy is achieved in a certain wide working speed range. The no-load motion accuracy is better than 0.6 mm with a manipulator whose length is 1.8 meter, and the motion error is less than 3 mm with loading of four kilograms.

On an effective design approach of cartesian space neural network control for robot manipulators

Robotica ◽  
1997 ◽  
Vol 15 (3) ◽  
pp. 305-312 ◽  
Author(s):  
Seul Jung ◽  
T. C. Hsia
Keyword(s):  
Neural Network ◽  
Position Control ◽  
Traditional Approach ◽  
Complex Problem ◽  
Network Control ◽  
Joint Torque ◽  
Reference Trajectory ◽  
Control Input ◽  
Cartesian Space ◽  
Training Signal

It is well known that computed torque robot control is subjected to performance degradation due to uncertainties in robot model, and application of neural network (NN) compensation techniques are promising. In this paper we examine the effectiveness of neural network (NN) as a compensator for the complex problem of Cartesian space control. In particular we examine the differences in system performance of accurate position control when the same NN compensator is applied at different locations in the controller structure. It is found that using NN to modify the reference trajectory to compensate for model uncertainties is much more effective than the traditional approach of modifying control input or joint torque/force. To facilitate the analysis, a new NN training signal is introduced and used for all cases. The study is also extended to non-model based Cartesian control problems. Simulation results with three-link rotary robot are presented and performances of different compensating locations are compared.

A high torque to weight ratio robot actuator

Robotica ◽  
1995 ◽  
Vol 13 (2) ◽  
pp. 201-208 ◽  
Author(s):  
James E. Bobrow ◽  
Jayesh Desai
Keyword(s):  
High Speed ◽  
Robot Control ◽  
Position Control ◽  
Weight Ratio ◽  
Experimental System ◽  
Gear Ratio ◽  
Torque Control ◽  
Joint Torque ◽  
Loop Control ◽  
High Torque

SummaryA light-weight, high-torque actuator with accurate torque control capability is described. The actuator uses a small hydrostatic transmission to achieve the advantage of large gear reduction from a high speed DC motor, and retains accurate joint torque sensing and control capabilities with no backlash. A disadvantage of the actuator is that is introduces extra dynamics which must be accounted for in robot control systems. It is shown that state feedback enables closed loop control of joint torque, with full back drivability, through an effective gear ratio of 485:1 for the experimental system. The actuator can therefore be used for both position control and output force control, which is essential for modern robot control algorithms. A mathematical model of the system is presented in this paper along with experimental results.

Adaptive Control of Harmonic Drives

2006 ◽  
Vol 129 (2) ◽  
pp. 182-193 ◽  
Author(s):  
Wen-Hong Zhu ◽  
Erick Dupuis ◽  
Michel Doyon
Keyword(s):  
Adaptive Control ◽  
Position Control ◽  
Robot Manipulator ◽  
Adaptive Controller ◽  
Torque Control ◽  
Joint Torque ◽  
Control Performance ◽  
Control Approach ◽  
Control Interface ◽  
Adaptive Control Algorithm

Aimed at achieving ultrahigh control performance for high-end applications of harmonic drives, an adaptive control algorithm using additional sensing, namely, the joint and motor positions and the joint torque, and their practically available time derivatives, is proposed. The proposed adaptive controller compensates the large friction associated with harmonic drives, while incorporating the dynamics of flexspline. The L2∕L∞ stability and the L2 gain-induced H∞ stability are guaranteed in both joint torque and joint position control modes. Conditions for achieving asymptotic stability are also given. The proposed joint controller can be efficiently incorporated into any robot motion control system based on either its torque control interface or the virtual decomposition control approach. Experimental results demonstrated in both the time and frequency domains confirm the superior control performance achieved not only in individual joint motion, but also in coordinated motion of an entire robot manipulator.

scholarly journals A Benchmarking of DCM-Based Architectures for Position, Velocity and Torque-Controlled Humanoid Robots

2020 ◽  
Vol 17 (01) ◽  
pp. 1950034
Author(s):  
Giulio Romualdi ◽  
Stefano Dafarra ◽  
Yue Hu ◽  
Prashanth Ramadoss ◽  
Francisco Javier Andrade Chavez ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Humanoid Robots ◽  
Torque Control ◽  
Whole Body ◽  
Simplified Model ◽  
Bipedal Robot ◽  
Robot Locomotion ◽  
Model Control ◽  
Walking Velocity ◽  
Control Layer

This paper contributes toward the benchmarking of control architectures for bipedal robot locomotion. It considers architectures that are based on the Divergent Component of Motion (DCM) and composed of three main layers: trajectory optimization, simplified model control, and whole-body quadratic programming (QP) control layer. While the first two layers use simplified robot models, the whole-body QP control layer uses a complete robot model to produce either desired positions, velocities, or torques inputs at the joint-level. This paper then compares two implementations of the simplified model control layer, which are tested with position, velocity, and torque control modes for the whole-body QP control layer. In particular, both an instantaneous and a Receding Horizon controller are presented for the simplified model control layer. We show also that one of the proposed architectures allows the humanoid robot iCub to achieve a forward walking velocity of 0.3372[Formula: see text]m/s, which is the highest walking velocity achieved by the iCub robot.

Robust Two-degree-of-freedom Control Based on H∞ Method for PMSM Drive System

2020 ◽  
Vol 13 (4) ◽  
pp. 496-506
Author(s):  
Qixin Zhu ◽  
Lei Xiong ◽  
Hongli Liu ◽  
Yonghong Zhu ◽  
Guoping Zhang
Keyword(s):  
Control System ◽  
Control Theory ◽  
Position Control ◽  
Dynamic Performance ◽  
Servo System ◽  
Degree Of Freedom ◽  
Trade Off ◽  
Standard Design ◽  
Position Controller ◽  
Two Degree Of Freedom

Background: The conventional method using one-degree-of-freedom (1DOF) controller for Permanent Magnet Synchronous Motor (PMSM) servo system has the trade-off problem between the dynamic performance and the robustness. Methods: In this paper, by using H∞ control theory, a novel robust two-degree-of-freedom (2DOF) controller has been proposed to improve the position control performance of PMSM servo system. Using robust control theory and 2DOF control theory, a H∞ robust position controller has been designed and discussed in detail. Results: The trade-off problem between the dynamic performance and robustness which exists in one-degree-of-freedom (1DOF) control can be dealt with by the application of 2DOF control theory. Then, through H∞ control theory, the design of robust position controller can be translated to H∞ robust standard design problem. Moreover, the control system with robust controller has been proved to be stable. Conclusion: Further simulation results demonstrate that compared with the conventional PID control, the designed control system has better robustness and attenuation to the disturbance of load impact.

CONTROL OF FOREARM MODULE IN UPPER-LIMB REHABILITATION ROBOT FOR REDUCTION AND BIOMECHANICAL ASSESSMENT OF PRONATOR HYPERTONIA OF STROKE PATIENTS

2016 ◽  
Vol 16 (02) ◽  
pp. 1650008 ◽  
Author(s):  
PIN-CHENG KUNG ◽  
CHOU-CHING K. LIN ◽  
SHU-MIN CHEN ◽  
MING-SHAUNG JU
Keyword(s):  
Upper Limb ◽  
Position Control ◽  
Biomechanical Properties ◽  
Torque Control ◽  
Rehabilitation Robot ◽  
Stroke Patients ◽  
Upper Limb Rehabilitation ◽  
Biomechanical Assessment ◽  
Custom Made ◽  
Limb Rehabilitation

Spastic hypertonia causes loss of range of motion (ROM) and contractures in patients with post-stroke hemiparesis. The pronation/supination of the forearm is an essential functional movement in daily activities. We developed a special module for a shoulder-elbow rehabilitation robot for the reduction and biomechanical assessment of pronator/supinator hypertonia of the forearm. The module consisted of a rotational drum driven by an AC servo motor and equipped with an encoder and a custom-made torque sensor. By properly switching the control algorithm between position control and torque control, a hybrid controller able to mimic a therapist’s manual stretching movements was designed. Nine stroke patients were recruited to validate the functions of the module. The results showed that the affected forearms had significant increases in the ROM after five cycles of stretching. Both the passive ROM and the average stiffness were highly correlated to the spasticity of the forearm flexor muscles as measured using the Modified Ashworth Scale (MAS). With the custom-made module and controller, this upper-limb rehabilitation robot may be able to aid physical therapists to reduce hypertonia and quantify biomechanical properties of the muscles for forearm rotation in stroke patients.

Multi-Objective Optimization of Human Gait With a Discomfort Function

2016 ◽  
Author(s):  
Hyun-Jung Kwon ◽  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Joint Torque ◽  
Upper Body ◽  
Whole Body ◽  
Human Gait ◽  
Multi Objective Optimization ◽  
Joint Angles ◽  
Backward Walking ◽  
Multi Objective ◽  
Body Model ◽  
Neutral Angle

The objective of this study was to develop a discomfort function for including a high DOF upper body model during walking. A multi-objective optimization (MOO) method was formulated by minimizing dynamic effort and the discomfort function simultaneously. The discomfort function is defined as the sum of the squares of deviation of joint angles from their neutral angle positions. The dynamic effort is the sum of the joint torque squared. To investigate the efficacy of the proposed MOO method, backward walking simulation was conducted. By minimizing both dynamic effort and the discomfort function, a 3D whole body model with a high DOF upper body for walking was demonstrated successfully.

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