Kinematic Control of Redundant Manipulators: Generalizing the Task-Priority Framework to Inequality Task

Kanoun, Oussama; Lamiraux, Florent; Wieber, P-B

doi:10.1109/tro.2011.2142450

Cited by 351 publications

(304 citation statements)

References 11 publications

Supporting

Mentioning

287

Contrasting

Unclassified

Order By: Relevance

“…staying within joint limits or avoiding obstacles) [15]. As recognized in [16], the multiple taskpriority inverse kinematics algorithm is not suitable to handle set-based tasks directly, and these tasks are therefore usually transformed into more restrictive equality constraints through potential fields or cost functions [17], [18].…”

Section: Introductionmentioning

confidence: 99%

“…A first attempt to systematically include set-based tasks in a prioritized task-regulation framework is proposed in [19] and further improved in [20]. To handle the set-based tasks, the algorithms in [19], [20] transform the inverse kinematics problem into a QP problem, and therefore they can not be utilized directly into the multiple task-priority inverse kinematics algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…To handle the set-based tasks, the algorithms in [19], [20] transform the inverse kinematics problem into a QP problem, and therefore they can not be utilized directly into the multiple task-priority inverse kinematics algorithm. In [21], set-based tasks are handled by resorting to proper activation and regularization functions, but has the limitation that set-based tasks are only considered with higher priority than the equality tasks of the system.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Experimental results for set-based control within the singularity-robust multiple task-priority inverse kinematics framework

Moe

Antonelli

Pettersen

et al. 2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

View full text Add to dashboard Cite

Abstract-Inverse kinematics algorithms are commonly used in robotic systems to achieve desired behavior, and several methods exist to ensure the achievement of numerous tasks simultaneously. The multiple task-priority inverse kinematics framework allows a consideration of tasks in a prioritized order by projecting task velocities through the null-spaces of higher priority tasks. Recent results have extended this framework from equality tasks to also handling set-based tasks, i.e. tasks that have an interval of valid values. The purpose of this paper is to further investigate and experimentally validate this algorithm and its properties. In particular, this paper presents experimental results where a number of both set-based and equality tasks have been implemented on the 6 Degree of Freedom UR5 which is an industrial robotic arm from Universal Robots. The experiments validate the theoretical results.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experimental results for set-based control within the singularity-robust multiple task-priority inverse kinematics framework

Moe

Antonelli

Pettersen

et al. 2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

View full text Add to dashboard Cite

show abstract

“…For instance, the Stack of Tasks approach (SoT) [20] provides an interface to add and remove tasks automatically with a pre-specified hierarchy. Recently, hierarchical control schemes based on a sequence of quadratic programs (QP) can also handle inequality constraints for kinematic control [21] and dynamic control [22]. Efforts have also been made to solve these problems fast enough for real-time control of humanoid robots with many degrees of freedom [23].…”

Section: Prioritized Controllersmentioning

confidence: 99%

Multi-contact haptic exploration and grasping with tactile sensors

Sommer

Billard

2016

Robotics and Autonomous Systems

View full text Add to dashboard Cite

Haptic exploration has received a great deal of attention of late thanks to the variety of commercially available tactile sensors. While the majority of previous works consider control of a single contact point at a time, we tackle simultaneous control of multiple contact points on several links. In addition, we use information from the existing tactile signals to increase the number of points in contact. We demonstrate the usefulness of this form of control to speed up exploration, scanning and to compliantly grasp unknown objects. Our controller requires to know only the parts of the robot on which it is desirable to make contact and does not need a model of the environment besides the robot itself. We validate the algorithm in a set of experiments using a robotic hand covered with tactile sensors and arm. In a grasping application, the active adaptation of the fingers to the shape of the object ensures that the hand encloses the object with multiple contact points. We show that this improves the robustness of the grasp compared to simple enclosing strategies. When combined with an exploration strategy, our multi-contact approach offers an efficient use of tactile sensors on the whole surface of robotic fingers, and enables the robot to perform a rapid exploration of complex, non convex shapes while maintaining low contact forces. It is robust to variation in the approach angle and to changes in the geometry and orientation of the object.

show abstract

“…As recognized in Kanoun et al (2011), inclusion of inequality constraints is still missing for the singularity-robust multiple taskpriority inverse kinematics framework. This paper aims to fill that gap.…”

Section: Introductionmentioning

confidence: 99%

Set-Based Tasks within the Singularity-Robust Multiple Task-Priority Inverse Kinematics Framework: General Formulation, Stability Analysis, and Experimental Results

et al. 2016

View full text Add to dashboard Cite

Inverse kinematics algorithms are commonly used in robotic systems to transform tasks to joint references, and several methods exist to ensure the achievement of several tasks simultaneously. The multiple task-priority inverse kinematics framework allows tasks to be considered in a prioritized order by projecting task velocities through the null spaces of higher-priority tasks. This paper extends this framework to handle set-based tasks, i.e., tasks with a range of valid values, in addition to equality tasks, which have a specific desired value. Examples of set-based tasks are joint limit and obstacle avoidance. The proposed method is proven to ensure asymptotic convergence of the equality task errors and the satisfaction of all high-priority set-based tasks. The practical implementation of the proposed algorithm is discussed, and experimental results are presented where a number of both set-based and equality tasks have been implemented on a 6 degree of freedom UR5, which is an industrial robotic arm from Universal Robots. The experiments validate the theoretical results and confirm the effectiveness of the proposed approach.

show abstract

Kinematic Control of Redundant Manipulators: Generalizing the Task-Priority Framework to Inequality Task

Cited by 351 publications

References 11 publications

Experimental results for set-based control within the singularity-robust multiple task-priority inverse kinematics framework

Experimental results for set-based control within the singularity-robust multiple task-priority inverse kinematics framework

Multi-contact haptic exploration and grasping with tactile sensors

Set-Based Tasks within the Singularity-Robust Multiple Task-Priority Inverse Kinematics Framework: General Formulation, Stability Analysis, and Experimental Results

Contact Info

Product

Resources

About