Redundancy Resolution With Multiple Criteria

Lee, Kwang-Kyu; Buss, Martin

doi:10.1109/iros.2006.282538

Cited by 20 publications

(12 citation statements)

References 14 publications

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“…GPM solves the inverse kinematics problem at the velocity level and can only deal with performance criteria defined at the position level. Besides, many other performance criteria such as velocity limit avoidance, peak torque avoidance, obstacle avoidance, mathematical singularity avoidance and energy minimization can be selected (Kapoor et al 1998 ;Lee & Buss 2006). Redundancy resolution can be at different levels, like joint displacements, velocities, acceleration or torques.…”

Section: Discussionmentioning

confidence: 99%

Inverse Kinematics and Control of a 7-DOF Redundant Manipulator Based on the Closed-Loop Algorithm

Wang

Zhao

2010

International Journal of Advanced Robotic Systems

103

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Closed-loop inverse kinematics (CLIK) algorithm mostly resolves the redundancy at the velocity level. In this paper we extend the CLIK algorithm to the acceleration level to meet some applications that require the joint accelerations. The redundancy resolutions at the velocities and acceleration levels via pseudoinverse method are analyzed respectively. The objective function of joint limits avoidance(JLA) is combined into the redundancy resolution as an optimization approach of the null space motion. A seven-DOF redundant manipulator is designed to do the computer simulations and the real experiments are carried out on a Powercube modular manipulator. Their results demonstrated the effectiveness of the proposed algorithm.

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Section: Discussionmentioning

confidence: 99%

Inverse Kinematics and Control of a 7-DOF Redundant Manipulator Based on the Closed-Loop Algorithm

Wang

Zhao

2010

International Journal of Advanced Robotic Systems

103

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“…The classical method consists of using the Moore-Penrose inverse matrix J ϩ (Liegeois, 1977) using the general solution: q ϭ J ϩ ẋ ϩ ␣(I Ϫ J ϩ J)ٌ⌽ with ٌ⌽ gradien to f⌽͑q͒ (3) where J ϩ ϭ J T (JJ T ) -1 denotes the pseudo inverse of J, I is the identity matrix, p⌽ is defined as the gradient of ⌽(q) and ␣ is the projection magnitude. This is constructed by aggregating the weighted criteria (Lee and Buss, 2006). It is defined by:…”

Section: Resolution Methodsmentioning

confidence: 99%

Redundancy-based optimization approach to optimize robotic cell behaviour: application to robotic machining

Sabourin

Subrin

Cousturier

et al. 2015

Industrial Robot: An International Journal

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Purpose – The robot offers interesting capabilities, but suffers from a lack of stiffness. The proposed solution is to introduce redundancies for the overall improvement of different capabilities. The management of redundancy associated with the definition of a set of kinematic, mechanical and stiffness criteria enables path planning to be optimized. Design/methodology/approach – The resolution method is based on the projection onto the kernel of the Jacobian matrix of the gradient of an objective function constructed by aggregating kinematic, mechanical and stiffness weighted criteria. Optimized redundancy management is applied to the 11-DoF (degrees of freedom) cells to provide an efficient placement of turntable and track. The final part presents the improvement of the various criteria applied to both 9-DoF and 11-DoF robotic cells. Findings – The first application concerns the optimized placement of a turntable and a linear track using 11-DoF architecture. Improved criteria for two 9-DoF robotic cells, a robot with parallelogram closed loop and a Tricept are also presented. Simulation results present the contributions of redundancies and the leading role of the track. Research limitations/implications – The redundancy-based optimization presented and the associated simulation approach must be completed by the experimental determination of the optimization criteria to take into account each machining strategy. Practical implications – This work in robotics machining relates to milling operations for automotive and aerospace equipment. The study is carried out within the framework of the RobotEx Equipment of Excellence programme. Originality/value – The resolution method to optimized path planning is applied to 9- and 11-DoF robotic cells, including a hybrid robot with a parallelogram closed loop and a Tricept PKM.

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“…On account of the hierarchical control structure applied by GPM considering multiple constraints-based performance criteria, excellent works have been conducted to avoid or alleviate the difficulty of inaccurate coefficients for performance criteria. A nested GPM [9] and [10] is used to provide fixed scalar weighted value for each performance criterion intuitively. Owing to the lack of adaptability to the changing situations using the fixed weighted values, a redundancy-based approach [11] is presented for GPM to eliminate the negative effect by iteratively solving a system of linear equations.…”

Section: Introductionmentioning

confidence: 99%

A Weighted Gradient Projection Method for Inverse Kinematics of Redundant Manipulators Considering Multiple Performance Criteria

2018

SV-JME

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Among the many methods of solving inverse kinematics (IK) of redundant manipulators, the classic weighted least-norm (WLN) method is often introduced to avoid joint position limits effectively but cannot be extended to restrict other constraints. Another general technique uses the fashioned gradient projection method (GPM) that ensures successes of the main task and the constraints-based subtasks but suffers with regard to the proper selections for the coefficients of performance criteria. Inspired by the merits of WLN and GPM, a weighted gradient projection method (WGPM) is proposed in this paper to resolve IK problems of redundant manipulators with multiple performance criteria. In this approach, its structure is formulated as a hierarchical task-level regulation, where the highest priority is to accomplish the main task higher than the avoidance of joint position limits, and the priorities of other subtasks of the performance criteria are dependent on the clamping weighted matrix in descending order. Moreover, to avoid the defect of selecting scalar factors for different criteria by trial and error in GPM, a technique of determining proper scalar coefficients is presented by means of normalizing corresponding performance functions in WGPM. Using a 7 degree-of-freedom (DOF) redundant manipulator, simulations and experiments are conducted to demonstrate the validity of the proposed WGPM method by comparing it with the results of the traditional WLN and GPM methods, respectively. Highlights• Multiple performance criteria are taken into account in resolving IK problems of redundant manipulators. • The hierarchical method can guarantee implementations of the main task and the subtasks. • A scalar coefficient of performance criterion is adjusted on-line by the normalization method. • The obtained results prove the effectiveness of the proposed WGPM method.

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Redundancy Resolution With Multiple Criteria

Cited by 20 publications

References 14 publications

Inverse Kinematics and Control of a 7-DOF Redundant Manipulator Based on the Closed-Loop Algorithm

Inverse Kinematics and Control of a 7-DOF Redundant Manipulator Based on the Closed-Loop Algorithm

Redundancy-based optimization approach to optimize robotic cell behaviour: application to robotic machining

A Weighted Gradient Projection Method for Inverse Kinematics of Redundant Manipulators Considering Multiple Performance Criteria

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