Task-directed inverse kinematics for redundant manipulators

Long, Mark K.

doi:10.1007/bf00248018

Cited by 8 publications

(10 citation statements)

References 18 publications

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“…In this paper, the user-define function  is distributed by 'arm angle', which describes the angle from reference plane and the shoulder-elbow-wrist plane SEW , as shown in Figure 4. The reference plane is consisted of y-axis of the basic frame and line SW [16]. The kinematic function and the differential function of the arm angle as:…”

Section: Modeling Of the Manipulatormentioning

confidence: 99%

Real-Time Obstacle Avoidance for Telerobotic Systems Based on Equipotential Surface

Song

et al. 2012

International Journal of Advanced Robotic Systems

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Redundant manipulators offer a dual advantage of flexibility and dexterity and can be used in many civilian and military areas. However, operating such systems by teleoperation is challenging because of the redundancy and unstructured task environment, which result in the human operator suffering a huge burden when telemanipulator is facing the complicated obstacles. The existing methods usually use some off-line algorithms to solve the problem of obstacle avoidance. It is difficult for them to meet the requirements of real-time teleoperation in some unknown environment. This paper presents an on-line method for a telerobotic system to take advantage of redundancy to avoid obstacle, which is based on realtime sensor information. With this method, the human operator can focus attention on the end-effector operation regardless of the obstacle avoidance of other parts. The effectiveness and advantage of the method are well demonstrated by experiments.

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Section: Modeling Of the Manipulatormentioning

confidence: 99%

Real-Time Obstacle Avoidance for Telerobotic Systems Based on Equipotential Surface

Song

et al. 2012

International Journal of Advanced Robotic Systems

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“…Although Jacobian inverse routines could be used, a damped least-squares inverse is used here to allow further task prioritization and singularity robustness [12,13,10,14,11]. The motion-space-velocity vector of the manipulator has three translational coordinates, three orientation coordinates and the ann angle.…”

Section: Impedance Control Using Real and Virtual Sensors 93mentioning

confidence: 99%

“…Augmented Jacobian methods focus on defining kinematic functions that provide forward and differential kinematic relationships to attempt to fully specify the motion of all degrees of freedom of the mechanism. These approaches have been fairly successful [1][2][3] but still have some difficulties. Often the forward kinematic relationships are difficult to compute and may not be defined over the entire workspace.…”

Section: Introductionmentioning

confidence: 98%

“…Additionally, the majority of these functions do not have closed-form Jacobian relationships and require numerical techniques for computation. Many of the problems with artificial singularities of these new kinematic functions and discontinuities in switching from one function or subtask have been addressed using damped least-squares for position controlled applications [4,1,2]. However, damped least-squares with joint velocity weighting introduces tracking error throughout the workspace and requires the selection of weighting matrices which is often non-intuitive.…”

Section: Introductionmentioning

confidence: 98%

“…The results are also applicable to other redundant and non-redundant manipulators with various numbers of DOFs. Previous work has described techniques for compliant motion control [5][6][7], shared control [8], and redundancy resolution [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extended impedance control using real and virtual sensors for redundant manipulators

Long

Backes

1995

J Intell Robot Syst

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Abstract. Control of a redundant manipulator based on an impedance-control framework with multiple simultaneous control sources is described. Each control source provides a different behavior type. An application is decomposed into multiple simultaneous behaviors whose resultant behavior will provide the motion necessary to execute the task. The simultaneous control inputs are merged using impedance control to compute a resultant command to the manipulator. The task space of each behavior can have the dimensionality of the mechanism being controlled. Control of a seven-degree-of-freedom manipulator is described here with an available task space for each behavior of dimensionality seven.

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Minimum effort factor approach for sensor‐based control of a four‐joint 6‐dof redundant manipulator

1994

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A sensor‐driven control model and a minimum effort control algorithm in terms of time and energy expended during the execution of a movement strategy are described and validated for a multijointed cooperating robotic manipulator. Considering smooth, human‐like (anthropomorphic) movements, using joint motion profiles achievable in real time as well as sensory information from all joints, and evaluating the total work expended by each manipulator joint during the execution of a movement strategy, a minimum effort motion trajectory is synthesized to precisely and efficiently position the robotic arm end‐effector. This sensor‐based approach significantly reduces the computational requirements for such cooperative motion. The minimum effort control algorithm generates several human‐like arm movement strategies and selects the best strategy on the basis of expendable effort. The algorithm has an inherent basis to deal with obstacles in an efficient way. Detailed examples are described from the simulation studies. © 1994 John Wiley & Sons, Inc.

show abstract

Task-directed inverse kinematics for redundant manipulators

Cited by 8 publications

References 18 publications

Real-Time Obstacle Avoidance for Telerobotic Systems Based on Equipotential Surface

Real-Time Obstacle Avoidance for Telerobotic Systems Based on Equipotential Surface

Extended impedance control using real and virtual sensors for redundant manipulators

Minimum effort factor approach for sensor‐based control of a four‐joint 6‐dof redundant manipulator

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