Redundancy Resolution Technique Research Articles

A multi-chamber soft robot for transesophageal echocardiography: continuous kinematic matching control of soft medical robots.

This research investigates designing a continuum soft robot and proposing a kinematic matching control to enable the robot to perform a specified medical task, which in this paper is the transesophageal echocardiography (TEE). A multi-chamber soft robot was designed and fabricated based on the molding of separate layers. The method of transformation matrices was used to develop the kinematic models, and a control method using Jacobian matrices was proposed to manipulate the robot. A prototype was made based on a multi-chamber multi-layer design. The system contains three segments that can be actuated independently to mimic the active bending part of the respective probe. Kinematic models were developed. Negative pressure (vacuum) was used as actuation input. An open-loop controller inspired by a redundancy resolution technique was proposed to make the soft robot tip follow the desired path, i.e.the path of the rigid ultrasound probe. It is concluded that the soft solution can perform the required task as the reachable points of the TEEtip cover the proposed robot workspace and the proposed control can be used for maneuvering in arbitrary trajectories.

A Robot Arm Design Optimization Method by Using a Kinematic Redundancy Resolution Technique

Redundancy resolution techniques have been widely used for the control of kinematically redundant robots. In this work, one of the redundancy resolution techniques is employed in the mechanical design optimization of a robot arm. Although the robot arm is non-redundant, the proposed method modifies robot arm kinematics by adding virtual joints to make the robot arm kinematically redundant. In the proposed method, a suitable objective function is selected to optimize the robot arm’s kinematic parameters by enhancing one or more performance indices. Then the robot arm’s end-effector is fixed at critical positions while the redundancy resolution algorithm moves its joints including the virtual joints because of the self-motion of a redundant robot. Hence, the optimum values of the virtual joints are determined, and the design of the robot arm is modified accordingly. An advantage of this method is the visualization of the changes in the manipulator’s structure during the optimization process. In this work, as a case study, a passive robotic arm that is used in a surgical robot system is considered and the task is defined as the determination of the optimum base location and the first link’s length. The results indicate the effectiveness of the proposed method.

Motion Planning and Coordinated Control of Underwater Vehicle-Manipulator Systems with Inertial Delay Control and Fuzzy Compensator

This paper presents new motion planning and robust coordinated control schemes for trajectory tracking of the underwater vehicle-manipulator system (UVMS) subjected to model uncertainties, time-varying external disturbances, payload and sensory noises. A redundancy resolution technique with a new secondary task and nonlinear function is proposed to generate trajectories for the vehicle and manipulator. In this way, the vehicle attitude and manipulator position are aligned in such a way that the interactive forces are reduced. To resist sensory measurement noises, an extended Kalman filter (EKF) is utilized to estimate the UVMS states. Using these estimates, a tracking controller based on feedback Linearization with both the joint-space and task-space tracking errors is proposed. Moreover, the inertial delay control (IDC) is incorporated in the proposed control scheme to estimate the lumped uncertainties and disturbances. In addition, a fuzzy compensator based on these estimates via IDC is introduced for reducing the undesired effects of perturbations. Trajectory tracking tasks on a five-degrees-of-freedom (5-DOF) underwater vehicle equipped with a 3-DOF manipulator are numerically simulated. The comparative results demonstrate the performance of the proposed controller in terms of tracking errors, energy consumption and robustness against uncertainties and disturbances.

A General User-Oriented Framework for Holonomic Redundancy Resolution in Robotic Manipulators Using Task Augmentation

Redundant robotic manipulators under kinematic control may exhibit unpredictable behaviors at the joint level. When the end effector describes a closed trajectory, the joint angles may not return to their initial values. Likewise, final configuration in the joint space may depend on the trajectory that is followed by the end effector. In this paper, a complete parameterization of holonomic redundancy resolution techniques that avoid these problems is proposed. The flexibility of the proposed approach is discussed. In particular, it is shown that the selection of the redundancy resolution criterion is totally decoupled from the implementation of a closed-loop inverse kinematics (CLIK) algorithm. Any user-defined redundancy resolution criterion can, thus, be enforced. Potentialities of this new methodology are experimentally verified on an industrial robot in a case study where functional redundancy occurs and is applied in simulation on a 7-degree-of-freedom (7-DOF) anthropomorphic manipulator.

An Empirical Approach to Performance Criteria for Manipulation

Empirical performance criteria based on geometric and physical properties are commonly used for real-time decision-making (and design) of redundant anthropomorphic manipulators (serial) or workcells (parallel) performing high level tasks while avoiding obstacles, providing safety, and responding to human commands. This requires configuration management of these complex systems by prioritizing candidate configurations relative to quantifiable secondary objectives with clear physical meanings. Clarity is addressed by using position, inertial, kinetic, and potential energy (gravity and deformation) based metrics that are crisply defined from system and input parameters. Scaling differences among derived performance metrics require normalization to determine their relative import and inclusion in multicriteria decision-making techniques. Large dimensional spaces mean statistically reduced representations are necessary to decipher their relative import and allow an operator without extensive robotic knowledge to use them effectively and independent of a redundancy resolution technique (RRT). We propose two global norms: the unit norm and the average norm for a broad set of performance criteria that quantify these systems’ unique constraint, transmission, and energy characteristics. These norms are then used to select relevant criteria for operational decision-making based on intuitive operator commands instead of abstract mathematical notions. Additionally, a modified RRT is presented that is more robust with respect to changes during operation in the secondary objectives, which allows for greater flexibility when formulating new criteria. Results are illustrated using a variety of new and existing criteria on an anthropomorphic dual-arm system.

複数の接地部分と冗長関節を有するヒューマノイドロボットの受動性に基づく最適接触力制御

This paper proposes a practical contact force control framework for force-controllable legged robots with redundant joints, which is applicable to automatic/semi-automatic control for mobile robots, construction robots, bipedal humanoid robots, and assisitive devices. The proposed method requires: (1) no contact forces measurements; (2) no inverse kinematics; (3) nor inverse dynamics in achieving the desired contact forces. Combined with a passivity-based redundancy resolution technique, a contact force closure is optimally solved and transformed directly into joint torques in real-time. Experimental results on a full-sized biped humanoid robot show that the proposed method can simultaneously control the multiple contact forces without generating internal forces, and can naturally interact with unknown external forces.

1P2-N-027 特異点通過軌道を用いた冗長運動制御法の比較(冗長自由度ロボット・メカニズムとその制御,生活を支援するロボメカ技術のメガインテグレーション)

1P2-N-027 特異点通過軌道を用いた冗長運動制御法の比較(冗長自由度ロボット・メカニズムとその制御,生活を支援するロボメカ技術のメガインテグレーション)

Singularity-robust task-priority redundancy resolution for real-time kinematic control of robot manipulators

Practical application of the task-priority redundancy resolution technique must deal with the occurrence of kinematic and algorithmic singularities. The aim of this paper is twofold. First, the application of existing singularity-robust methods to the case of kinematically redundant arms is studied. Then, a new task-priority redundancy resolution technique is developed that overcomes the effects of algorithmic singularities. Computational aspects of the solutions are also considered in view of real-time implementation of a kinematic control algorithm. The method is applied to a seven-degree-of-freedom manipulator in numerical case studies to demonstrate its effectiveness.

Overview of damped least-squares methods for inverse kinematics of robot manipulators

In this paper, we present a tutorial report of the literature on the damped-least squares method which has been used for computing velocity inverse kinematics of robotic manipulators. This is a local optimization method that can prevent infeasible joint velocities near singular configurations by using a damping factor to control the norm of the joint velocity vector. However, the exactness of the inverse kinematic solution has to be sacrificed in order to achieve feasibility. The damping factor is an important parameter in this technique since it determines the trade-off between the accuracy and feasibility of the inverse kinematic solution. Various methods that have been proposed to compute an appropriate damping factor are described. Redundant manipulators, possessing extra degrees of freedom, afford more choice of inverse kinematic solutions than do non-redundant ones. The damped least-squares method has been used in conjunction with redundancy resolution schemes to compute feasible joint velocities for redundant arms while performing an additional subtask. We outline the different techniques that have been proposed to achieve this objective. In addition, we introduce an iterative method to compute the optimal damping factor for one of the redundancy resolution techniques.

Dynamic redundancy resolution of redundant manipulators with local optimization of a kinematic criterion

To consider the dynamic effects of redundancy resolution in redundant manipulators, the inverse kinematics of the redundant manipulator must be resolved at the acceleration level, focussing mainly on using selective dynamic criteria to resolve the redundancy. These local dynamic redundancy resolution techniques reveal some instability problems due to the high joint velocities. The buildup of high joint velocities is due to the lack of a kinematic criterion in the local optimization process to reflect the changes of joint velocities. In order to avoid instability due to high joint velocities, this paper proposes dynamic redundancy resolution techniques (SMV and SMTV) which locally optimize the performance function, including a kinematic criterion as the norm of joint velocities to reflect the changes of joint velocities. These prevent the occurrence of high joint velocities and guarantee that joint velocities at end of motion are near zero. In addition, the redundancy is resolved at the joint acceleration level to consider the manipulator dynamics and the effect of kinematic criterion on the manipulator joint torques. Computer simulations were performed on a three-link planar rotary manipulator to verify the performance of the proposed dynamic redundancy resolution techniques and to compare its performance with existing local dynamic redundancy resolution techniques.

Task-priority redundancy resolution with robustness to algorithmic singularities

The task-priority strategy allows redundancy resolution by adding a null-space motion to the basic pseudoinverse joint velocity solution such that the fulfillment of the given primary task is not affected while attempting to satisfy also a secondary task. A problem with this technique is related to the occurrence of algorithmic singularities at which the null-space motion required to achieve the secondary task may give infeasible joint velocities; this represents a severe limitation on practical applicability of the method. In this paper a task-priority redundancy resolution technique is introduced which is suitably devised to properly handle the occurrence of algorithmic singularities. The method is applied to a simple three-degree-of-freedom planar manipulator in numerical case studies to illustrate its potential in comparison to the existing techniques.

Restricted Jacobian Matrices of Redundant Manipulators in Constrained Motion Tasks

Kinematically redundant manipulators are considered, with a prespecified end-effector task and multiple additional tasks. The number of additional tasks is assumed to be equal to or less than the degree of redundancy. This assumption justifies an equal-priority (or duality) concept for the end-effector task and additional tasks. Based on this concept, expressions for two restricted Jacobian matrices are derived: the restricted manipulator Jacobian and the restricted additional-task Jaco bian. It is shown that generalized inverses of these matrices can be utilized to derive two alternative solutions of instanta neous inverse kinematics that satisfy both tasks simultaneously. The first solution, which is based on the null space of the manipulator Jacobian, has been widely applied in various redundancy-resolution techniques; it is shown that when used in manipulator self-motion tasks, this solution yields cyclic- path motion in joint space. The second solution utilizes the null space of the additional-task Jacobian; it is dual to the first one. Hence, in the particular case of end-effector motion with additional-task maintenance, this solution yields cyclic-path motion as well. It is further shown that at algorithmic singularities, both restricted Jacobian matrices lose rank simultaneously. Algo rithmic singularities, together with the well-known manipulator singularities, and newly defined additional-task singularities are shown to play an important role in kinematic analysis. The duality concept calls for the definition of a new type of dexterity measure: the additional-task performance measure. The restricted Jacobian matrices are shown to also provide a convenient tool for deriving "restricted" dexterity measures that are directly related to the various types of singularities. Typical end-effector/additional-task combinations have been tested through computer simulation, illustrating the application of the restricted Jacobian matrices to configuration analy sis and path-planning problems of redundant manipulators in constrained-motion tasks.

A Fuzzy Backstepping Control of a Mobile Manipulator with Torque Limits Avoidance

In this paper, we present a dynamic redundancy resolution technique for mobile manipulator subject to joint torque limits. First, the dynamic model of the mobile manipulator in feasible motion space is given. Next, a control algorithm is proposed which completely decouples the motion of the system into the end-effector motion in the task space and an internal motion in the null space and controls them in prioritized basis with priority given to the primary task space and enables the selection of characteristics in both subspaces separately. A special attention is given to the joints torque limits avoidance where a new weighted pseudo-inverse of the Jacobian that accounts for both inertia and torque limits is proposed to solve problems inherent to torque limits of the system. Simulation results are given to illustrate the coordination of two subsystems in executing the desired trajectory without violating the joint torque limits.