Robust walking stabilization strategy of humanoid robots on uneven terrain via QP-based impedance/admittance control

Jo, Joonhee; Park, Gyunghoon; Oh, Yonghwan

doi:10.1016/j.robot.2022.104148

Cited by 11 publications

(4 citation statements)

References 10 publications

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“…Besides, both types may be necessary in the same task, thus a hybrid formulation should be investigated. This is considered in Jo et al (2022), to perform robust walking stabilization on uneven terrain for humanoid robots, where a QP-based hybrid impedance/admittance control is formulated via reference modification. However, a single task is defined since no hierarchical scheme is considered and the results are evaluated only in simulation.…”

Section: Contributionsmentioning

confidence: 99%

Multi-Modal and Adaptive Control of Human-Robot Interaction through Hierarchical Quadratic Programming

Tassi

Ajoudani

2023

Preprint

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This paper proposes a novel Hierarchical Quadratic Programming (HQP)-based framework that enables multi-tasking control under multiple Human-Robot Interaction (HRI) scenarios. The objective is to create a unique framework for various types of HRI control modalities, avoiding the necessity of switching between different controllers that are usually tailored to a specific task. To achieve this, we firstly propose a HQP-based hybrid Cartesian/joint space impedance control formulation. This is based on the system's dynamics and provides an adaptive compliance behaviour during HRI, while performing hierarchical motion control. This is validated through a series of experiments that show the accuracy of trajectory tracking and the variable compliance behaviour. We then consider the case in which the human needs to move the robot by acting directly onto it, by proposing a hybrid admittance/impedance hierarchical control, which is then validated through several experiments in which the human moves the robot in the workspace. Next, we formulate a HQP-based force controller for HRI applications in which a specific interaction force must be maintained and lastly, we extend this to simultaneous force and trajectory tracking for applications that need higher position accuracy. Further experiments are conducted, to validate the proposed framework, using a redundant mobile manipulator. Overall, we obtain a single multi-purpose HQP-based control framework, that can switch continuously between interaction modes, enclosing multiple behaviours adjusted online based on the type of interaction.

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Section: Contributionsmentioning

confidence: 99%

Multi-Modal and Adaptive Control of Human-Robot Interaction through Hierarchical Quadratic Programming

Tassi

Ajoudani

2023

Preprint

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“…Firstly, we propose a hybrid Cartesian/joint space impedance controller that includes system's dynamics to provide a variable impedance behaviour. With respect to existing works that only employ either Cartesian [30,31] or joint-space [32,13] impedance behaviour, we propose a hybrid formulation in hierarchical form, in which the Cartesian impedance is injected via robot's kinematics and is regulated by its dynamics, whereas joint-space impedance is injected at a lower level, via torques. All of this, is written in HQP form, which enables relative prioritization and ensures constraints satisfaction.…”

Section: Contributionsmentioning

confidence: 99%

“…Besides, both types may be necessary in the same task, thus a hybrid formulation needs to be investigated. This is considered in [30], to perform robust walking stabilization on uneven terrain for humanoid robots, where a QP-based hybrid impedance/admittance control is formulated via reference modification. However, a single task is defined, since no hierarchical features are considered and the results are evaluated only in simulation.…”

Section: Contributionsmentioning

confidence: 99%

Multi-Modal and Adaptive Robot Control through Hierarchical Quadratic Programming

Tassi

Ajoudani

2023

Preprint

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This paper proposes a novel Hierarchical Quadratic Programming (HQP)-based framework that enables multi-tasking control under multiple Human-Robot Interaction (HRI) scenarios. The proposed theoretical formulation of the controller is inspired by real-world contact-rich scenarios, which currently constitute one of the main applicability limits of most theoretical controllers. Indeed, HRI can occur through different modalities, based on human's needs. The objective is to create a unique framework for various types of interaction, avoiding the necessity of switching between different control types that are typically tailored for a specific task. To achieve this, we firstly propose a HQP-based hybrid Cartesian/joint space impedance control formulation. Based on system's dynamics, this provides an adaptive compliance behaviour of the robot, while performing hierarchical motion control. This is validated through a series of experiments that show the accuracy of trajectory tracking and the variable compliance behaviour. We then consider the case in which the human needs to move the robot directly, by proposing a hybrid admittance/impedance hierarchical control, which is validated through several experiments in which the human easily moves the robot in the workspace via interaction. Next, we formulate a HQP-based force controller through which a specific interaction force can be maintained and lastly, we extend this to simultaneous force and trajectory tracking. Overall, we obtain a multi-purpose HQP-based control framework, that can switch continuously between interaction modes, enabling multiple hierarchical behaviours that can cover a wide spectrum of interaction types, essential for synergistic HRI.

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“…Additional issue as faced by heavy-duty industrial applications then unearthed insufficient sensitivity, antinoise, and anti-vibration across specifications of a comprehensive sensory setup. Majority of the sensory arrangement across contemporary medium scale robots have utilized force sensors as mounted on specific regions such as the tips, joints and body for external force detection [11][12][13][14], alongside the complementation of alternative sensory approaches such as vision sensors [15][16][17][18]. Nevertheless, readied hydraulic and pneumatic robots for such heavy-duty industrial tasks would require additional setup and monetary Complex mechanical structure of default robotic design then concurred the impractical, inefficient and difficult nature of installing build-to-order contact sensing devices [19].…”

Section: Introductionmentioning

confidence: 99%

Interaction Motion Control on Tri-finger Pneumatic Grasper using Variable Convergence Rate Prescribed Performance Impedance Control with Pressure-based Force Estimator

Irawan

Azahar

Pebrianti

2022

Journal of Robotics and Control

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Pneumatic robot is a fluid dynamic based robot system which possesses immense uncertainties and nonlinearities over its electrical driven counterpart. Requirement for dynamic motion handling further challenged the implemented control system on both aspects of interaction and compliance control. This study especially set to counter the unstable and inadaptable proportional motions of pneumatic robot grasper towards its environment through the employment of Variable Convergence Rate Prescribed Performance Impedance Control (VPPIC) with pressure-based force estimation (PFE). Impedance control was derived for a single finger of Tri-finger Pneumatic Grasper (TPG) robot, with improvement being subsequently made to the controller’s output by appropriation of formulated finite-time prescribed performance control. Produced responses from exerted pressure of the maneuvered pneumatic piston were then recorded via derived PEE with adherence to both dynamics and geometry of the designated finger. Validation of the proposed method was proceeded on both circumstances of human hand as a blockage and ping-pong ball as methodical representation of a fragile object. Developed findings confirmed relatively uniform force sensing ability for both proposed PEE and load sensor as equipped to the robot’s fingertip with respect to the experimented thrusting and holding of a human hand. Sensing capacity of the estimator has also advanced beyond the fingertip to enclose its finger in entirety. Whereas stable interaction control at negligible oscillation has been exhibited from VPPIC against the standard impedance control towards gentle and compression-free handling of fragile objects. Overall positional tracking of the finger, thus, justified VPPIC as a robust mechanism for smooth operation amid and succeed direct object interaction, notwithstanding its transcendence beyond boundaries of the prescribed performance constraint.

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Robust walking stabilization strategy of humanoid robots on uneven terrain via QP-based impedance/admittance control

Cited by 11 publications

References 10 publications

Multi-Modal and Adaptive Control of Human-Robot Interaction through Hierarchical Quadratic Programming

Multi-Modal and Adaptive Control of Human-Robot Interaction through Hierarchical Quadratic Programming

Multi-Modal and Adaptive Robot Control through Hierarchical Quadratic Programming

Interaction Motion Control on Tri-finger Pneumatic Grasper using Variable Convergence Rate Prescribed Performance Impedance Control with Pressure-based Force Estimator

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