Stability-Guaranteed Impedance Control of Hydraulic Robotic Manipulators

Koivumäki, Janne; Mattila, Jouni

doi:10.1109/tmech.2016.2618912

Cited by 96 publications

(76 citation statements)

References 35 publications

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“…This study shows that stability-guaranteed NMB control methods can provide the most advanced control performance for highly nonlinear hydraulic manipulators. The study further shows that the authors' stability-guaranteed NMB controls demonstrate the state-of-the-art for hydraulic manipulators' free-space motion (see [16]) and constrained motion (see [7], [8]) controls.…”

Section: Related Workmentioning

confidence: 64%

“…Overall, the proposed method is built on the authors' earlier contributions on high-precision and stability-guaranteed n-DOF manipulator controls [7], [8], [16] and on LfD algorithms [13], [26]. Furthermore, the solution relies on an advanced force-reflected teleoperation method in [27], which is compatible to the hydraulic manipulator control methods in [7], [8], [16]. The proposed method consists of four important parts, i.e, control system design, contact force estimation, bilateral teleoperation and learning algorithm.…”

Section: Methodsmentioning

confidence: 99%

“…However, automatic planning of compliant motions is shown to be mathematically infeasible [5]. Furthermore, designing a stability-guaranteed (i.e., theoretically sound) and high-precision closed-loop control for multiple degrees-of-freedom (n-DOF) hydraulic manipulators is a well-known challenge due to their highly nonlinear dynamic behaviour [3], [6]- [8]. It is valid to mention that the control system stability is the primary requirement for all control systems and an unstable system is typically useless and potentially dangerous [9], [10].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we show that despite the significant challenges, it is possible to realize LfD capabilities for hydraulic manipulators using a force-reflected bilateral teleoperation that allows an arbitrary motion and force scaling between the manipulators. Furthermore, the proposed method takes an advantage of a novel LfD method [13] which is incorporated to a novel impedance control method [8] to learn compliant behaviour from teleoperated human demonstrations. The use of a fragile force sensor at the contact point is avoided by estimating the contact forces from the hydraulic cylinders' chamber pressures [7].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Learning from Demonstration for Hydraulic Manipulators

Suomalainen¹,

Koivumäki

Lampinen

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents, for the first time, a method for learning in-contact tasks from a teleoperated demonstration with a hydraulic manipulator. Due to the use of extremely powerful hydraulic manipulator, a force-reflected bilateral teleoperation is the most reasonable method of giving a human demonstration. An advanced subsystem-dynamic-based control design framework, virtual decomposition control (VDC), is used to design a stability-guaranteed controller for the teleoperation system, while taking into account the full nonlinear dynamics of the master and slave manipulators. The use of fragile force/ torque sensor at the tip of the hydraulic slave manipulator is avoided by estimating the contact forces from the manipulator actuators' chamber pressures. In the proposed learning method, it is observed that a surface-sliding tool has a friction-dependent range of directions (between the actual direction of motion and the contact force) from which the manipulator can apply force to produce the sliding motion. By this intuition, an intersection of these ranges can be taken over a motion to robustly find a desired direction for the motion from one or more demonstrations. The compliant axes required to reproduce the motion can be found by assuming that all motions outside the desired direction is caused by the environment, signalling the need for compliance. Finally, the learning method is incorporated to a novel VDC-based impedance control method to learn compliant behaviour from teleoperated human demonstrations. Experiments with 2-DOF hydraulic manipulator with a 475kg payload demonstrate the suitability and effectiveness of the proposed method to perform learning from demonstration (LfD) with heavy-duty hydraulic manipulators.

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Section: Related Workmentioning

confidence: 64%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Learning from Demonstration for Hydraulic Manipulators

Suomalainen¹,

Koivumäki

Lampinen

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Self Cite

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show abstract

“…We considered some external disturbances while training the operator. This platform is able to serve as a preliminary validation tool to test the motion control methods of ROVs and manipulators in the real world (Jun et al, 2008;Koivumäki and Mattila, 2016;Shim et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Study of manipulator operations maneuvered by a ROV in virtual environments

Jin

Wei

et al. 2017

Ocean Engineering

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Autonomous robotic rock breaking using a real‐time 3D visual perception system

Lampinen

Niu

Hulttinen

et al. 2021

Journal of Field Robotics

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Crushing of blasted ore is an essential phase in extraction of valuable minerals in mining industry. It is typically performed in multiple stages with each stage producing finer fragmentation. Performance and throughput of the first stage of crushing is highly dependent on the size distribution of the blasted ore. In the crushing plant, a metal grate prevents oversized boulders from getting into the crusher jaws, and a human-controlled hydraulic manipulator equipped with a rock hammer is required to break oversized boulders and ensure continuous material flow. This secondary breaking task is event-based in the sense that ore trucks deliver boulders at irregular intervals, thus requiring constant human supervision to ensure continuous material flow and prevent blockages. To automatize such breaking tasks, an intelligent robotic control system along with a visual perception system (VPS) is essential. In this manuscript, we propose an autonomous breaker system that includes a VPS capable of detecting multiple irregularly shaped rocks, a robotic control system featuring a decision-making mechanism for determining the breaking order when dealing with multiple rocks, and a comprehensive manipulator control system. We present a proof of concept for an autonomous robotic boulder breaking system, which consists of a stereo-camera-based VPS and an industrial rock-breaking manipulator robotized with our retrofitted system design. The experiments in this study were conducted in a real-world setup, and the results were evaluated based on the success rates of breaking. The experiments yielded an average success rate of 34% and a break pace of 3.3 attempts per minute.

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Stability-Guaranteed Impedance Control of Hydraulic Robotic Manipulators

Cited by 96 publications

References 35 publications

Learning from Demonstration for Hydraulic Manipulators

Learning from Demonstration for Hydraulic Manipulators

Study of manipulator operations maneuvered by a ROV in virtual environments

Autonomous robotic rock breaking using a real‐time 3D visual perception system

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