Robust adaptive control of coordinated multiple mobile manipulators

Li, Zhijun; Ge, Shuzhi Sam; Wang, Zhuping

doi:10.1016/j.mechatronics.2008.01.001

Cited by 84 publications

(41 citation statements)

References 15 publications

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“…Regarding manipulation of rigid objects by multiple robots, several approaches have been proposed. Either centralized: using feedback control [4] or potential fields [5]; or distributed using caging [6], force sensing [7], or leader following [8] combined with force sensing. We borrow the idea of force sensing, but consider it only when the object reaches a limit in deformation.…”

Section: B Assumptions and Limitationsmentioning

confidence: 99%

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Local motion planning for collaborative multi-robot manipulation of deformable objects

Alonso–Mora¹,

Knepper

Siegwart

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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This paper presents a formalism that exploits deformability during manipulation of soft objects by robot teams. A hybrid centralized/distributed approach restricts centralized planning to high-level global guidance of the object for consensus. Low-level control is thus delegated to the individual manipulator robots, which retain manipulation and collision avoidance guarantees by passing forces to one another through the object. A distributed receding horizon planner provides local control, formulated as a convex optimization problem in velocity space and incorporating constraints for both collision avoidance and shape maintenance. We demonstrate teams of mobile manipulators autonomously carrying various deformable objects.

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Section: B Assumptions and Limitationsmentioning

confidence: 99%

“…We assume f (∆v) = f and f −1 (f) = ∆v/2. The factor is added to avoid over reaction and oscillations 4. Other conventions are possible, such as constant neighbor's velocity.…”

mentioning

confidence: 99%

Local motion planning for collaborative multi-robot manipulation of deformable objects

Alonso–Mora¹,

Knepper

Siegwart

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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“…A considerable amount of work on multiple robotic systems has been performed during the last few decades [9][10][11][12][13][14][15]. Mostly, the position and/or force control of multiple manipulators handling a rigid object were studied in [9][10][11].…”

Section: Issues and Prior Researchmentioning

confidence: 99%

“…Mostly, the position and/or force control of multiple manipulators handling a rigid object were studied in [9][10][11]. However, there were some works on handling deformable object by multiple manipulators presented in [12][13][14][15]…”

Section: Issues and Prior Researchmentioning

confidence: 99%

Target Point Manipulation Inside a Deformable Object

Das¹,

Sarkar²

2012

Robotic Systems - Applications, Control and Programming

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“…However, to the best of our knowledge, most of the existing research on the cyclic motion is about the single manipulator [7], [8] or for the biped walking [10]. This is because more complex tasks and constraints need to be considered in multiple robot systems [11]- [14], for instance, the robust coordinated motion. A common characteristic of these studies is to consider the coordinated motion, and the robots are manipulators or mobile manipulators.…”

mentioning

confidence: 99%

Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots

Zhang

et al. 2015

IEEE Trans. Neural Netw. Learning Syst.

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126

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We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.

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Robust adaptive control of coordinated multiple mobile manipulators

Cited by 84 publications

References 15 publications

Local motion planning for collaborative multi-robot manipulation of deformable objects

Local motion planning for collaborative multi-robot manipulation of deformable objects

Target Point Manipulation Inside a Deformable Object

Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots

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