Compliant Motion Control Research Articles

Compliant Motion Control of Wheel-Legged Humanoid Robot on Rough Terrains

Compliant Motion Control of Wheel-Legged Humanoid Robot on Rough Terrains

Bioinspired Rigid-Flexible Coupled Adaptive Compliant Motion Control of Robot Gecko for Space Stations.

This paper presents a study on bioinspired rigid-flexible coupling adaptive compliant motion control of a robot gecko with hybrid actuation for space stations. The biomimetic robot gecko is made of a rigid trunk, four motor-driven active legs with dual-degree-of-freedom shoulder joints, and four pneumatic flexible pleated active attachment-detachment feet. The adaptive impedance model consists of four input parameters: the inertia coefficient, stiffness coefficient, damping coefficient, and segmented expected plantar force. The robot gecko is equipped with four force sensors mounted on its four feet, from which the normal force of each foot can be sensed in real-time. Based on the sensor signal, the variable stiffness characteristics of the feet in different states are analyzed. Furthermore, an adaptive active compliance control strategy with whole-body rigidity-flexibility-force feedback coupling is proposed for the robot gecko. Four sets of experiments are presented, including open-loop motion control, static anti-interference experiment, segmented variable stiffness experiment, and adaptative compliant motion control, both in a microgravity environment. The experiment results indicated that the presented control strategy worked well and the robot gecko demonstrates the capability of stable attachment and compliant detachment, thereby normal impact and microgravity instability are avoided. It achieves position tracking and force tracking while exhibiting strong robustness for external disturbances.

Deep-Learning-Based Compliant Motion Control of a Pneumatically-Driven Robotic Catheter

In cardiovascular interventions, when steering catheters and especially robotic catheters, great care should be paid to prevent applying too large forces on the vessel walls as this could dislodge calcifications, induce scars or even cause perforation. To address this challenge, this paper presents a novel compliant motion control algorithm that relies solely on position sensing of the catheter tip and knowledge of the catheter’s behavior. The proposed algorithm features a data-driven tip position controller. The controller is trained based on a so-called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">control Long Short-Term Memory Network</i> (control-LSTM). Trajectory following experiments are conducted to validate the quality of the proposed control-LSTM. Results demonstrated superior positioning capability with sub-degree precision of the new approach in the presence of severe rate-dependent hysteresis. Experiments both in a simplified setup as well as in an aortic phantom further show that the proposed approach allows reducing the interaction forces with the environment by around 70%. This work shows how deep learning can be exploited advantageously to avoid tedious modeling that would be needed to precisely steer continuum robots in constrained environments such as the patient’s vasculature.

Lio-A Personal Robot Assistant for Human-Robot Interaction and Care Applications.

Lio is a mobile robot platform with a multi-functional arm explicitly designed for human-robot interaction and personal care assistant tasks. The robot has already been deployed in several health care facilities, where it is functioning autonomously, assisting staff and patients on an everyday basis. Lio is intrinsically safe by having full coverage in soft artificial-leather material as well as collision detection, limited speed and forces. Furthermore, the robot has a compliant motion controller. A combination of visual, audio, laser, ultrasound and mechanical sensors are used for safe navigation and environment understanding. The ROS-enabled setup allows researchers to access raw sensor data as well as have direct control of the robot. The friendly appearance of Lio has resulted in the robot being well accepted by health care staff and patients. Fully autonomous operation is made possible by a flexible decision engine, autonomous navigation and automatic recharging. Combined with time-scheduled task triggers, this allows Lio to operate throughout the day, with a battery life of up to 8 hours and recharging during idle times. A combination of powerful computing units provides enough processing power to deploy artificial intelligence and deep learning-based solutions on-board the robot without the need to send any sensitive data to cloud services, guaranteeing compliance with privacy requirements. During the COVID-19 pandemic, Lio was rapidly adjusted to perform additional functionality like disinfection and remote elevated body temperature detection. It complies with ISO13482 - Safety requirements for personal care robots, meaning it can be directly tested and deployed in care facilities.

Mechanical Impedance Control of Cooperative Robot During Object Manipulation Based on External Force Estimation Using Recurrent Neural Network

This paper proposes a compliant motion control for human-cooperative robots to absorb collision force when persons accidentally touch the robots even while the robot is manipulating an object. In the proposed method, an external force estimator, which can distinguish the net external force from the object manipulation force, is realized using an inverse dynamics model acquired by a recurrent neural network (RNN). By implementing a mechanical impedance control to the estimated external force, the robot can quickly and precisely carry the object keeping the mechanical impedance control functioned and can generate a compliant motion to the net external force only when the person touches it during manipulation. Since the proposed method estimates the external force from the generalized force based on the learned inverse dynamics, it is not necessary to install any sensors on the manipulated object to measure the external force. This allows the robot to detect the collision even when the person touches anywhere on the manipulated object. The RNN inverse dynamics model is evaluated by the leave-one-out cross-validation and it was found that it works well for unknown trajectories excluded from the learning process. Although the details were omitted due to the limitation of the page length, similar to the simulations, the RNN inverse dynamics model was evaluated using unknown trajectories in the six degree-of-freedom experiments, and it has been verified that it functions properly even for the unknown trajectories. Finally, the validity of the proposed method has been confirmed by experiments in which a person touches a robot while it is manipulating an object with six degrees of freedom.

Distributed computation and control of robot motion dynamics on FPGAs

Driven by advances in miniaturized electronics, many robotic systems today consist of modular hardware components. This leads to numerous computing units that are distributed within such systems. In order to make better use of such hardware structures from a computational point of view, the implementation of classical control approaches should be reconsidered. Following this idea, a method for distributed computation of motion dynamics of robotic systems using Field Programmable Gate Arrays is discussed. In this approach, local low-level actuator controllers are regarded as interconnected nodes, which are aware of their actuated degree of freedom and the resulting motion of the attached rigid body link element. A modified recursive Newton–Euler algorithm is computed by these nodes, where each node only exchanges data with the neighboring nodes. In the computations, a linear dependency on the dynamic parameters is kept in order to simplify the direct use of dynamic parameters estimated from experimental data. Implementation details and experimental results using a robotic manipulator arm are presented. The experiments show that the method allows compliant motion control. Payloads and external forces acting on a link are considered in the distributed computation of the model by informing the node controlling the respective link of the additional forces.

A sEMG-Based Shared Control System With No-Target Obstacle Avoidance for Omnidirectional Mobile Robots

We propose a novel shared control strategy for mobile robots in a human-robot interaction manner based on surface eletromyography (sEMG) signals. For security reasons, an obstacle avoidance scheme is introduced to the shared control system as collision avoidance guidance. The motion of the mobile robot is a resultant of compliant motion control and obstacle avoidance. In the mode of compliant motion, the sEMG signals obtained from the operator's forearms are transformed into human commands to control the moving direction and linear velocity of the mobile robot, respectively. When the mobile robot is blocked by obstacles, the motion mode is converted into obstacle avoidance. Aimed at the obstacle avoidance problem without a specific target, we develop a no-target Bug (NT-Bug) algorithm to guide the mobile robot to avoid obstacles and return to the command line. Besides, the command moving direction given by the operator is taken into consideration in the obstacle avoidance process to plan a smoother and safer path for the mobile robot. A model predictive controller is exploited to minimize the tracking errors. Experiments have been implemented to demonstrate the effectiveness of the proposed shared control strategy and the NT-Bug algorithm.

Serpens: A Highly Compliant Low-Cost ROS-Based Snake Robot with Series Elastic Actuators, Stereoscopic Vision and a Screw-Less Assembly Mechanism

Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory-perceptual system to perceive the surrounding operational environment for means of propulsion is defined as perception-driven obstacle-aided locomotion (POAL). From a control point of view, achieving POAL with traditional rigidly-actuated robots is challenging because of the complex interaction between the snake robot and the immediate environment. To simplify the control complexity, compliant motion and fine torque control on each joint is essential. Accordingly, intrinsically elastic joints have become progressively prominent over the last years for a variety robotic applications. Commonly, elastic joints are considered to outperform rigid actuation in terms of peak dynamics, robustness, and energy efficiency. Even though a few examples of elastic snake robots exist, they are generally expensive to manufacture and tailored to custom-made hardware/software components that are not openly available off-the-shelf. In this work, Serpens, a newly-designed low-cost, open-source and highly-compliant multi-purpose modular snake robot with series elastic actuator (SEA) is presented. Serpens features precision torque control and stereoscopic vision. Only low-cost commercial-off-the-shelf (COTS) components are adopted. The robot modules can be 3D-printed by using Fused Deposition Modelling (FDM) manufacturing technology, thus making the rapid-prototyping process very economical and fast. A screw-less assembly mechanism allows for connecting the modules and reconfigure the robot in a very reliable and robust manner. The concept of modularity is also applied to the system architecture on both the software and hardware sides. Each module is independent, being controlled by a self-reliant controller board. The software architecture is based on the Robot Operating System (ROS). This paper describes the design of Serpens and presents preliminary simulation and experimental results, which illustrate its performance.

The Applications of Compliant Motion Control Technique on 6-DOF Hydraulic Parallel Mechanism

Most interaction control formulations focused on electrically driven parallel mechanism. In this paper, the combining practice applications of compliant motion control technique on six degrees of freedom (6-DOF) hydraulic parallel mechanism (HPM) are investigated. According to the manipulation task specification and hydraulic control system characteristics, three different compliant motion control schemes are presented in three typical application scenarios, respectively: a parallel position/force control scheme in the joint space coordinate for train curve negotiation performance test, a hybrid position/force control scheme with the internal force suppression for shaking table with actuation redundancy, and a hybrid impedance control scheme for auto-docking mechanism based on force and vision. The feasibility and effectiveness of the proposed schemes were verified through a series of experiments. It showed that the 6-DOF HPM achieves good compliant behavior by applying the proposed compliant motion control techniques. These schemes could also be extended to other applications where the compliant motion of the 6-DOF HPM is required.

Shared Control Design of a Walking-Assistant Robot

This brief presents a control design for a walking-assistant robot in a complex indoor environment, such that it can assist a walking-impaired person to walk and avoid unexpected obstacles. In this design, the robot motion is a resultant of autonomous navigation and compliant motion control. The compliance motion controller allows the robot to possess passive behavior following the motion intent of the user, while the autonomous guidance gives safe navigation of the robot without colliding with any obstacles. A shared-control approach is suggested to combine the passive compliant behavior and safe guidance of the robot. When a user exerts force to the robot, the mobile platform responds to adjust the speed in compliance with the user movement. On the other hand, the autonomous navigation controller is designed to provide collision-free guidance. Using the developed shared controller, outputs of the compliance motion controller and autonomous navigation controller are fused to generate appropriate motion for the robot. In this manner, passive behavior allows the walking-assistant robot to adapt to a user’s motion intent and move in compliance with user. Meanwhile, the active guidance adjusts the linear velocity and the direction of the robot in real time in response to the environmental data received from the on-board laser scanner. The developed algorithms have been implemented on a self-constructed walking-assistant robot. Experimental results validate the proposed design and demonstrate that the robot can actively avoid unexpected obstacles while move passively following the user to the destination.

Terrain edge detection for biped walking robots using active sensing with vCoP-position hybrid control

Perception of terrain is one of the most important technical impediments for biped robots to locomote in human environments. Perception error exists due to imperfect exteroceptive devices causing issues such as limited viewing angles or occlusion of visual sensors. This error can cause unexpected contact between the robot and the environment. The reaction wrenches from unexpected contact negatively affect the control and balance of the biped robot. In this study, active sensing method is proposed to estimate the edges of the contact terrain using robot link geometry information. By generating proper active motion that maintains the contact, the geometric information of the contact link is collected to estimate the edge of the contact terrain. To recognize contact and calculate its geometry, a multi-modal sensory strategy with 6 degrees of freedom (DOF) force/torque sensors at robot ankles and joint encoders is proposed. The concept of virtual Center-of-Pressure (vCoP) is utilized to generate active motion of the foot while maintaining the contact. To prevent loss of balance during active motion, the normal force condition of the vCoP is taken into account and the contact moment of the supporting foot is controlled. The operational space control scheme for a floating-base robot is adopted to apply compliant motion and vCoP-position hybrid control framework. The proposed method is verified by experiments using a 12-DOF biped robot to estimate the edge line of a block that has contact with the robot foot.

Prototyping Force-Controlled 3-DOF Hydraulic Arms for Humanoid Robots

[abstFig src='/00280001/11.jpg' width=""230"" text='Hydraulic dual arm robot prototype' ]This paper reports on a hydraulic dual arm robot developed as a rapid prototype for our hydraulic humanoid robot. The lightweight arms (4 kg each) have three joints driven by hydraulic linear servo actuators that can achieve higher torque and speed than human arms. A double four-bar linkage provides a wide range of motion (210°) to the shoulder joint. Each joint has torque controllability that is fully utilized for compliant whole-body motion control tasks. Based on singular perturbation analysis, we discuss how damping on the joints is actively modulated by hydraulic force feedback control, which is then utilized in our passivity-based task-space force control scheme. The effectiveness of the proposed system is experimentally evaluated through zero-force tracking gravity compensation with a 10 kg payload and object manipulation tasks.

Joint position-based impedance control with load compensation for robot arm

As part of compliant motion control for a robot arm, the force sensor is usually installed at the wrist of the robot arm to measure the force/moment caused by the external force and the load (the end-effector and the extra object). The robot arm will fail to achieve the desired compliance if the effect of the load is not considered. In this study, a strategy of joint position-based impedance control with load compensation method for the robot arm is proposed, even if the load is unknown. It will distinguish between the external force and the gravitational effect of the load in compliant motion control. Experimental results show that the proposed control method can successfully remove the effect caused by the load, and the robot arm performs compliant motion correctly, in accordance with the impedance characteristic.

Compliant Motion Control for Multisegment Continuum Robots With Actuation Force Sensing

During exploration through tortuous unstructured passages by continuum robots, methods are required to minimize the force interaction between the environment and the robot along its length. This paper presents and evaluates an algorithm for compliant motion control of continuum robots subjected to multiple unknown contacts with the environment. A mapping of external wrenches to a generalized force in the configuration space of a multisegment continuum robot is presented and related to measured joint-level actuation forces. These measurements are applied as inputs to a low-level compliant motion controller. Friction and modeling uncertainties, presenting an unknown nonlinear deviation from the nominal system model, are corrected via a feed-forward estimate provided by a support vector machine. The controller is evaluated on O9 and O5 mm multisegment continuum robots. We quantify the minimal interaction forces needed to generate compliant motion and demonstrate the ability of the controller to minimize interaction forces during insertion through tortuous passages.

Dynamic compensation by fusing a high-speed actuator and high-speed visual feedback with its application to fast peg-and-hole alignment

This paper presents a dynamic compensation concept to grapple with the dynamic defects of a traditional robot arm, especially while performing high-speed endpoint regulations. The proposed high-speed dynamic compensation concept offers a new point of view for cooperating with a traditional manipulator to realize highly dexterous performance of manipulations. The concept is realized through adoption of a high-speed light-weight actuator as well as endpoint closed loop configured high-speed cameras. The dynamic compensation is analyzed experimentally with 1000 Hz visual feedback and a high-speed finger for a robot arm in the case of one degree of freedom. The advantage of the proposed approach is that the modeling for the robot system’s dynamics is not needed, whereas it is necessary and trivial in order to realize high-speed regulations by traditional approaches. Thus, the control issue becomes easier with the proposed approach. As an application for this concept, fast peg-and-hole alignment with large position and attitude uncertainty is studied. The alignment algorithm is based on a visual compliance strategy. Alignment experiments show that with the proposed concept of dynamic compensation as well as visual compliant motion control, robust and fast convergence was realized for most cases.

An active sensing strategy for contact location without tactile sensors using robot geometry and kinematics

In this study, we develop new techniques to sense contact locations and control robots in contact situations in order to enable articulated robotic systems to perform manipulations and grasping actions. Active sensing approaches are investigated by utilizing robot kinematics and geometry to improve upon existing sensing methods for contact. Compliant motion control is used so that a robot can actively search for and localize the desired contact location. Robot control in a contact situation is improved by the precise estimation of the contact location. From this viewpoint, we investigate a new control strategy to accommodate the proposed sensing techniques in contact situations. The proposed estimation algorithm and the control strategy both work complementarily. Then, we verify the proposed algorithm through experiments using 7-DOF hardware and a simulation environment. The two major contributions of the proposed active sensing strategy are the estimation algorithm for contact location without any tactile sensors, and the control strategy complementing the proposed estimation algorithm.

Compliant Motion Control for Handling a Single Object by Two Similar Industrial Robots

In this paper, we propose a compliant motion control strategy for handling a single object by two similar industrial robots. The dynamics of the object carried by the two robots is assimilated to the dynamics of a mass-spring-damper system described by a piecewise linear model (PWA). The coordination of the two robots is accomplished using a master slave synchronization approach dedicated for PWA systems, based on the Lyapunov theory, and solved via Linear Matrix Inequalities (LMIs). The performances of the proposed approach are proved by simulation results and compared to a related approach with larger stability criteria.

Stiffness and Impedance Control Using Lyapunov Theory for Robot-Aided Rehabilitation

In this paper, stiffness and impedance control concepts are used to solve position and force control for robot-aided rehabilitation. New asymptotic stability conditions are proposed using a suitable Lyapunov approach and based on the relationship between the dynamics of the robot and its energy. The efficiency of the proposed approach is tested on a planar 3 DOF robot-aided rehabilitation constrained to a circular trajectory. The robotic device is configured to be safe and stable in compliant motion in contact with the human arm. It is also designed to be adapted easily to different subjects for performing different tasks. Force and control parameters are tuned using a non linear optimization strategy for which the stability conditions are considered as inequality constraints. Simulation results show that the robot could guide the upper limb of subjects in circular movements under predefined model of the external force and prove the stability and the performances of the compliant motion control strategy.

Admittance Control using a Base Force/Torque Sensor.

In this paper we investigate on the use of a base force/torque sensor for implementing position based impedance control (i.e. admittance control). By utilizing measurements of the contact force at the base of a robot manipulator, it is possible to perceive forces acting all along the robot's structure. This can be used for implementing a compliant motion control algorithm which is not limited to physical interaction at the end-effector only. We show that the use of a base force sensor instead of a sensor mounted on the end-effector poses certain limitations on the achievable closed loop dynamics. The stability and passivity properties are exemplified by an analysis for the one-degree-of-freedom case. The control performance in the multi-degrees-of-freedom case is verified by a simulation study of a Cartesian admittance controller.

Active Compliant Motion Control for Grinding Robot

A grinding robot system is presented in this paper. Active compliant motion control is applied to keep contacting between grinding tool and work pieces and auto surface tracking algorithm was developed to trace the outline of work-pieces. For real implementation of the system, the shape of work pieces are informed through barcode and the piece's dimension is measured with a laser distance sensor. Experimental results with the implemented system are also presented and discussions for further works are followed.