Stiffness Control of Parallel Continuum Robots

2018 ◽  
Author(s):  
Vincent Aloi ◽  
Caroline Black ◽  
Caleb Rucker
Keyword(s):  
Position Control ◽  
Target Position ◽  
Human Robot Interaction ◽  
Force Measurements ◽  
Modeling Framework ◽  
Continuum Robots ◽  
Integral Control ◽  
Control Approach ◽  
Cosserat Rods ◽  
Stiffness Control

Parallel continuum robots can provide compact, compliant manipulation of tools in robotic surgery and larger-scale human robot interaction. In this paper we address stiffness control of parallel continuum robots using a general nonlinear kinetostatic modeling framework based on Cosserat rods. We use a model formulation that estimates the applied end-effector force and pose using actuator force measurements. An integral control approach then modifies the commanded target position based on the desired stiffness behavior and the estimated force and position. We then use low-level position control of the actuators to achieve the modified target position. Experimental results show that after calibration of a single model parameter, the proposed approach achieves accurate stiffness control in various directions and poses.

scholarly journals Force/position control of a robot manipulator for human-robot interaction

2016 ◽  
Vol 20 (suppl. 2) ◽  
pp. 537-548 ◽  
Author(s):  
Paramin Neranon ◽  
Robert Bicker
Keyword(s):  
Control System ◽  
Real Time ◽  
Position Control ◽  
Force Measurement ◽  
Robot Manipulator ◽  
Robotic System ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Integral Control ◽  
Proportional Integral

With regard to both human and robot capabilities, human-robot interaction provides several benefits, and this will be significantly developed and implemented. This work focuses on the development of real-time external force/position control used for human-robot interaction. The force-controlled robotic system integrated with proportional integral control was performed and evaluated to ensure its reliably and timely operational characteristics, in which appropriate proportional integral gains were experimentally adopted using a set of virtual crank-turning tests. The designed robotic system is made up of a robot manipulator arm, an ATI Gamma multi-axis force/torque sensor and a real-time external PC based control system. A proportional integral controller has been developed to provide stable and robust force control on unknown environmental stiffness and motion. To quantify its effectiveness, the robotic system has been verified through a comprehensive set of experiments, in which force measurement and ALTER real-time path control systems were evaluated. In summary, the results indicated satisfactorily stable performance of the robot force/position control system. The gain tuning for proportional plus integral control algorithm was successfully implemented. It can be reported that the best performance as specified by the error root mean square method of the radial force is observed with proportional and integral gains of 0.10 and 0.005 respectively.

Modeling and Control of a Hybrid Wheeled Legged Robot: Disturbance Analysis

2020 ◽  
Author(s):  
Fahad Raza ◽  
Dai Owaki ◽  
Mitsuhiro Hayashibe
Keyword(s):  
Position Control ◽  
Control Method ◽  
System Modeling ◽  
Linear Quadratic Regulator ◽  
Human Robot Interaction ◽  
Physical Disorder ◽  
Legged Robot ◽  
Linear Quadratic ◽  
Control Approach ◽  
Lqr Control

Abstract The most common cause of injuries among older adults is falling. Recently, there have been numerous developments in assistive and exoskeleton systems. However, comparatively little work is being done on systems that may help people to keep an upright position and avoid falling over. In this preliminary work, we investigate the feasibility of the wheel-legged robot as a balance-assist system for the people who cannot maintain balance and walk because of an injury, old age, or neurological or physical disorder. We perform motion stability analyses of the wheel-legged robot under different conditions such as system modeling errors, sensor noise, and external disturbances. The linear quadratic regulator (LQR) control approach is adopted for balancing, steering, and translational position control of the robot. To validate our control framework and visualize results, the robot is modeled and tested in the Gazebo simulator using ROS (Robot Operating System). Subsequently, the simulation results demonstrate the effectiveness of the LQR control method under the translational and rotational pushes of the wheel-legged system for human-robot interaction.

scholarly journals Position Control for Soft Actuators, Next Steps toward Inherently Safe Interaction

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1116
Author(s):  
Dongshuo Li ◽  
Vaishnavi Dornadula ◽  
Kengyu Lin ◽  
Michael Wehner
Keyword(s):  
Visual Servoing ◽  
Position Control ◽  
Low Cost ◽  
Deformation Characteristic ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Soft Robots ◽  
Great Opportunity ◽  
Control Approach ◽  
Soft Actuators

Soft robots present an avenue toward unprecedented societal acceptance, utility in populated environments, and direct interaction with humans. However, the compliance that makes them attractive also makes soft robots difficult to control. We present two low-cost approaches to control the motion of soft actuators in applications common in human-interaction tasks. First, we present a passive impedance approach, which employs restriction to pneumatic channels to regulate the inflation/deflation rate of a pneumatic actuator and eliminate the overshoot/oscillation seen in many underdamped silicone-based soft actuators. Second, we present a visual servoing feedback control approach. We present an elastomeric pneumatic finger as an example system on which both methods are evaluated and compared to an uncontrolled underdamped actuator. We perturb the actuator and demonstrate its ability to increase distal curvature around the obstacle and maintain the desired end position. In this approach, we use the continuum deformation characteristic of soft actuators as an advantage for control rather than a problem to be minimized. With their low cost and complexity, these techniques present great opportunity for soft robots to improve human–robot interaction.

Design and Compliant Control of a Piggyback Transfer Robot

2021 ◽  
pp. 1-54
Author(s):  
Yuxin Liu ◽  
Shijie Guo ◽  
Yuting Yin ◽  
Zhiwen Jiang ◽  
Teng Liu
Keyword(s):  
Subjective Evaluation ◽  
Objective Evaluation ◽  
Patient Transfer ◽  
Test Results ◽  
Passive Stiffness ◽  
Control Approach ◽  
Challenging Tasks ◽  
Compliant Control ◽  
Stiffness Control ◽  
Transfer Tasks

Abstract Patient transfer, such as lifting and moving a bedridden patient from a bed to a wheelchair or a pedestal pan, is one of the most physically challenging tasks in nursing care. Although many transfer devices have been developed, they are rarely used because of the large time consumption in performing transfer tasks and the lack of safety and comfortableness. We developed a piggyback transfer robot that can conduct patient transfer by imitating the motion when a person holds another person on his/her back. The robot consisted of a chest holder that moves like a human back. In this paper, we present an active stiffness control approach for the motion control of the chest holder, combined with a passive cushion, for lifting a care-receiver comfortably. A human-robot dynamic model was built and a subjective evaluation was conducted to optimize the parameters of both the active stiffness control and the passive cushion of the chest holder. The test results of 10 subjects demonstrated that the robot could transfer a subject safely and the combination of active stiffness and passive stiffness were essential to a comfortable transfer. The objective evaluation demonstrated that an active stiffness of k= 4 kPa/mm along with a passive stiffness lower than the stiffness of human chest was helpful for a comfort feeling.

scholarly journals Inter-trial effects in priming of pop-out: Comparison of computational updating models

2021 ◽  
Vol 17 (9) ◽  
pp. e1009332
Author(s):  
Fredrik Allenmark ◽  
Ahu Gokce ◽  
Thomas Geyer ◽  
Artyom Zinchenko ◽  
Hermann J. Müller ◽  
...  
Keyword(s):  
Model Comparison ◽  
Response Times ◽  
Target Position ◽  
Preceding Trial ◽  
Target Color ◽  
Model Parameters ◽  
Target Feature ◽  
Modeling Framework ◽  
Trial Effect ◽  
Starting Point

In visual search tasks, repeating features or the position of the target results in faster response times. Such inter-trial ‘priming’ effects occur not just for repetitions from the immediately preceding trial but also from trials further back. A paradigm known to produce particularly long-lasting inter-trial effects–of the target-defining feature, target position, and response (feature)–is the ‘priming of pop-out’ (PoP) paradigm, which typically uses sparse search displays and random swapping across trials of target- and distractor-defining features. However, the mechanisms underlying these inter-trial effects are still not well understood. To address this, we applied a modeling framework combining an evidence accumulation (EA) model with different computational updating rules of the model parameters (i.e., the drift rate and starting point of EA) for different aspects of stimulus history, to data from a (previously published) PoP study that had revealed significant inter-trial effects from several trials back for repetitions of the target color, the target position, and (response-critical) target feature. By performing a systematic model comparison, we aimed to determine which EA model parameter and which updating rule for that parameter best accounts for each inter-trial effect and the associated n-back temporal profile. We found that, in general, our modeling framework could accurately predict the n-back temporal profiles. Further, target color- and position-based inter-trial effects were best understood as arising from redistribution of a limited-capacity weight resource which determines the EA rate. In contrast, response-based inter-trial effects were best explained by a bias of the starting point towards the response associated with a previous target; this bias appeared largely tied to the position of the target. These findings elucidate how our cognitive system continually tracks, and updates an internal predictive model of, a number of separable stimulus and response parameters in order to optimize task performance.

Accurate Position Control of a Pneumatic Actuator

1990 ◽  
Vol 112 (4) ◽  
pp. 734-739 ◽  
Author(s):  
Jiing-Yih Lai ◽  
Chia-Hsiang Menq ◽  
Rajendra Singh
Keyword(s):  
Control Strategy ◽  
Pulse Width Modulation ◽  
Position Control ◽  
Integral Control ◽  
Pneumatic Actuators ◽  
Actuator Dynamics ◽  
Position Accuracy ◽  
Modulation Mode ◽  
Nonlinear Mechanical ◽  
Accurate Position

We propose a new control strategy for on-off valve controlled pneumatic actuators and robots with focus on the position accuracy. A mathematical model incorporating pneumatic process nonlinearities and nonlinear mechanical friction has been developed to characterize the actuator dynamics; this model with a few simplifications is then used to design the controller. In our control scheme, one valve is held open and the other is operated under the pulse width modulation mode to simulate the proportional control. An inner loop utilizing proportional-plus-integral control is formed to control the actuator pressure, and an outer loop with displacement and velocity feedbacks is used to control the load displacement. Also, a two staged feedforward force is implemented to reduce the steady state error due to the nonlinear mechanical friction. Experimental results on a single-degree-of-freedom pneumatic robot indicate that the proposed control system is better than the conventional on-off control strategy as it is effective in achieving the desired position accuracy without using any mechanical stops in the actuator.

System identification and robust position control for electro-hydraulic servo system using hybrid model predictive control

2017 ◽  
Vol 24 (18) ◽  
pp. 4145-4159 ◽  
Author(s):  
Hai-Bo Yuan ◽  
Hong-Cheol Na ◽  
Young-Bae Kim
Keyword(s):  
System Identification ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Position Control ◽  
Servo System ◽  
Model Parameters ◽  
Integral Control ◽  
Hybrid Controller ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

This paper examined system identification using grey-box model estimation and position-tracking control for an electro-hydraulic servo system (EHSS) using hybrid controller composed of proportional-integral control (PIC) and model predictive control (MPC). The nonlinear EHSS model is represented by differential equations. We identify model parameters and verify their accuracy against experimental data in MATLAB to evaluate the validity of this mathematical model. To guarantee improved performance of EHSS and precision of cylinder position, we propose a hybrid controller composed of PIC and MPC. The controller is designed using the Control Design and Simulation module in the Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW). A LabVIEW-based experimental rig is developed to apply the proposed controller in real time. Then, the validity and performance superiority of the hybrid controller were confirmed by comparing them with the MPC and PIC results. Results of real-life experiments show improved robustness and dynamic and static properties of EHSS.

Enabling impedance-based physical human–multi–robot collaboration: Experiments with four torque-controlled manipulators

2021 ◽  
pp. 027836492110536
Author(s):  
Niels Dehio ◽  
Joshua Smith ◽  
Dennis L. Wigand ◽  
Pouya Mohammadi ◽  
Michael Mistry ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Contact Forces ◽  
Torque Control ◽  
Human Interaction ◽  
Physical Interaction ◽  
Complex Situation ◽  
Control Approach ◽  
Model Based ◽  
Compliant Control ◽  
Multi Robot

Robotics research into multi-robot systems so far has concentrated on implementing intelligent swarm behavior and contact-less human interaction. Studies of haptic or physical human-robot interaction, by contrast, have primarily focused on the assistance offered by a single robot. Consequently, our understanding of the physical interaction and the implicit communication through contact forces between a human and a team of multiple collaborative robots is limited. We here introduce the term Physical Human Multi-Robot Collaboration (PHMRC) to describe this more complex situation, which we consider highly relevant in future service robotics. The scenario discussed in this article covers multiple manipulators in close proximity and coupled through physical contacts. We represent this set of robots as fingers of an up-scaled agile robot hand. This perspective enables us to employ model-based grasping theory to deal with multi-contact situations. Our torque-control approach integrates dexterous multi-manipulator grasping skills, optimization of contact forces, compensation of object dynamics, and advanced impedance regulation into a coherent compliant control scheme. For this to achieve, we contribute fundamental theoretical improvements. Finally, experiments with up to four collaborative KUKA LWR IV+ manipulators performed both in simulation and real world validate the model-based control approach. As a side effect, we notice that our multi-manipulator control framework applies identically to multi-legged systems, and we execute it also on the quadruped ANYmal subject to non-coplanar contacts and human interaction.

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