Control of rolling contacts in multi-arm manipulation

Paljug, E.; Yun, Xiaoping; Kumar, Vijay

doi:10.1109/70.313095

Cited by 112 publications

(45 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Once the backbone curve is determined for an assumed location of the end-effector, depending on the physical implementation morphology of a particular manipulator, various fitting algorithms can be developed. This method has been utilized to form the foundation for obstacle avoidance [10], locomotion [11], and motion control [12], [13]. Some researchers have shown the application of the modal ap- The authors are with the Department of Mechanical Engineering, Villanova University, Villanova, PA 19085 USA (e-mail: farbod.fahimi@villanova.edu; hashem.ashrafiuon@villanova.edu; c.nataraj@villanova.edu).…”

Section: An Improved Inverse Kinematic and Velocity Solution For Spatmentioning

confidence: 99%

“…When two or three robots are tightly coupled together in a specified formation for a specified manipulation task, the control problem is well-defined and the feedback control laws for coordinating a small team of robots are reasonably well understood [11]- [13]. The feedback laws for coordinated control of manipulation and locomotion are discussed by [14], [15].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Control of cooperating mobile manipulators

Sugar

Kumar

2002

IEEE Trans. Robot. Automat.

Self Cite

152

View full text Add to dashboard Cite

We describe a framework and control algorithms for coordinating multiple mobile robots with manipulators focusing on tasks that require grasping, manipulation and transporting large and possibly flexible objects without special purpose fixtures. Because each robot has an independent controller and is autonomous, the coordination and synergy are realized through sensing and communication. The robots can cooperatively transport objects and march in a tightly controlled formation, while also having the capability to navigate autonomously. We describe the key aspects of the overall hierarchy and the basic algorithms, with specific applications to our experimental testbed consisting of three robots. We describe results from many experiments that demonstrate the ability of the system to carry flexible boards and large boxes as well as the system's robustness to alignment and odometry errors. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Control of Cooperating Mobile ManipulatorsThomas G. Sugar and Vijay KumarAbstract-We describe a framework and control algorithms for coordinating multiple mobile robots with manipulators focusing on tasks that require grasping, manipulation and transporting large and possibly flexible objects without special purpose fixtures. Because each robot has an independent controller and is autonomous, the coordination and synergy are realized through sensing and communication. The robots can cooperatively transport objects and march in a tightly controlled formation, while also having the capability to navigate autonomously. We describe the key aspects of the overall hierarchy and the basic algorithms, with specific applications to our experimental testbed consisting of three robots. We describe results from many experiments that demonstrate the ability of the system to carry flexible boards and large boxes as well as the system's robustness to alignment and odometry errors.

show abstract

Section: An Improved Inverse Kinematic and Velocity Solution For Spatmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Control of cooperating mobile manipulators

Sugar

Kumar

2002

IEEE Trans. Robot. Automat.

Self Cite

152

View full text Add to dashboard Cite

show abstract

“…In order to ensure rolling motion, by definition, the tangential components of the relative linear velocities between the arms and the object at each contact point must be zero, that is (25) (26) (27) (28) Additionally, if the component of the relative angular velocity along the contact normal is zero, we achieve what is called pure rolling. If we impose this no-spin condition on the relative angular velocity we get (29) (30) Equations (25)- (30) are nonholonomic constraints.…”

Section: B Constraint Analysismentioning

confidence: 99%

“…The difference between the results of [6], [15] and this paper is that we are able to control the trajectory of contact points as well as the position/orientation of the object. Paljug et al [25], [24] demonstrated the control of rolling and contact forces in multiarm manipulation for two dimensional objects. But since rolling in two dimensions introduces only holonomic constraints, the problem was much simpler.…”

Section: Previous Workmentioning

confidence: 99%

Dynamic control of 3-D rolling contacts in two-arm manipulation

Sarkar

Yun

Kumar

1997

IEEE Trans. Robot. Automat.

Self Cite

106

View full text Add to dashboard Cite

When two or more arms are used to manipulate a large object, it is preferable not to have a rigid grasp in order to gain more dexterity in manipulation. It may therefore be necessary to control contact motion between the object and the effector(s) on one or more arms. This paper addresses the dynamic control of two arms cooperatively manipulating a large object with rolling contacts. In the framework presented here, the motion of the object as well as the loci of the contact point either on the surface of each effector or on the object can be directly controlled. The velocity and acceleration equations for three-dimensional rolling contacts are derived in order to obtain a dynamic model of the system. A nonlinear feedback control algorithm that decouples and linearizes the system is developed. This is used to demonstrate the control of rolling motion along each arm and the adaptation of grasps to varying loads. KeywordsDextrous manipulation, grasping, rolling contact, two-arm manipulation. Disciplines Engineering | Mechanical Engineering CommentsSuggested Citation: Sarkar, N., X. Yun and V. Kumar (1997 Abstract-When two or more arms are used to manipulate a large object, it is preferable not to have a rigid grasp in order to gain more dexterity in manipulation. It may therefore be necessary to control contact motion between the object and the effector(s) on one or more arms. This paper addresses the dynamic control of two arms cooperatively manipulating a large object with rolling contacts. In the framework presented here, the motion of the object as well as the loci of the contact point either on the surface of each effector or on the object can be directly controlled. The velocity and acceleration equations for three-dimensional rolling contacts are derived in order to obtain a dynamic model of the system. A nonlinear feedback control algorithm that decouples and linearizes the system is developed. This is used to demonstrate the control of rolling motion along each arm and the adaptation of grasps to varying loads.

show abstract

“…Paljug et al (1994) investigated the problem of multi-arm manipulation. Erdmann (1998a) showed how to manipulate a known object with two palms.…”

Section: Nonprehensile Manipulationmentioning

confidence: 99%

Reconstructing shape from motion using tactile sensors

Moll

Erdmann

Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics I

View full text Add to dashboard Cite

We present a new method to reconstruct the shape of an unknown object using tactile sensors without requiring object immobilization. Instead, the robot manipulates the object without prehension. The robot infers the shape, motion and center of mass of the object based on the motion of the contact points as measured by tactile sensors. Our analysis is supported by simulation and experimental results.

show abstract

Control of rolling contacts in multi-arm manipulation

Cited by 112 publications

References 36 publications

Control of cooperating mobile manipulators

Control of cooperating mobile manipulators

Dynamic control of 3-D rolling contacts in two-arm manipulation

Reconstructing shape from motion using tactile sensors

Contact Info

Product

Resources

About