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Chapter 10 — Redundant Robots

Stefano Chiaverini, Giuseppe Oriolo and Anthony A. Maciejewski

This chapter focuses on redundancy resolution schemes, i. e., the techniques for exploiting the redundant degrees of freedom in the solution of the inverse kinematics problem. This is obviously an issue of major relevance for motion planning and control purposes.

In particular, task-oriented kinematics and the basic methods for its inversion at the velocity (first-order differential) level are first recalled, with a discussion of the main techniques for handling kinematic singularities. Next, different firstorder methods to solve kinematic redundancy are arranged in two main categories, namely those based on the optimization of suitable performance criteria and those relying on the augmentation of the task space. Redundancy resolution methods at the acceleration (second-order differential) level are then considered in order to take into account dynamics issues, e.g., torque minimization. Conditions under which a cyclic task motion results in a cyclic joint motion are also discussed; this is a major issue when a redundant manipulator is used to execute a repetitive task, e.g., in industrial applications. The use of kinematic redundancy for fault tolerance is analyzed in detail. Suggestions for further reading are given in a final section.

KUKA LBR iiwa - Kinematic Redundancy

Author  KUKA Roboter GmbH

Video ID : 813

The video shows the robot dexterity achieved by kinematic redundancy and illustrates the basic concept of self-motion (here called null-space motion).

Free-floating autonomous valve turning (task-priority redundancy control + Task Concurrence)‬

Author  CIRS UdG

Video ID : 814

This video records the experimental validation of a controller for the GIRONA500 underwater vehicle manipulator system demonstrating an autonomous floating-base valve-turning manipulation application. The method is based on kinematic control, avoiding the need for a complex, and difficult-to-obtain, hydrodynamic model. The method relies on the decoupled control of the vehicle and manipulator velocities using a combination of the task-priority redundancy resolution and the task concurrence approaches.

Human inspired tele-impedance and minimum-effort controller for improved manipulation Performance‬

Author  IIT Videos

Video ID : 815

Humans incorporate and switch between learnt neuro-motor strategies while performing complex tasks. To this purpose, kinematic redundancy is exploited in order to achieve optimized performance. Inspired by the superior motor skills of humans, in this work, we investigate a combined free-motion and contact-efficient controller in a certain class of robotic manipulation. In this multiple-criteria controller, kinematic degrees of redundancy are adapted according to task-suitable dynamic costs. The proposed algorithm attributes high priority to a minimum-effort controller while performing point-to-point, free-space movements. Once the robot comes into contact with the environment, the tele-impedance, common mode stiffness (CMS)-configuration dependent stiffness (CDS) controller will replicate the human's estimated endpoint stiffness and measured equilibrium-position profiles in the slave robotic arm, in real-time.

Human robot arm with redundancy resolution

Author  PRISMA Lab

Video ID : 816

In this video, the mapping of human-arm motion to an anthropomorphic robot arm (7-DOF Kuka LWR ) using Xsens MVN is demonstrated. The desired end-effector trajectories of the robot are reconstructed from the human hand, forearm and upper arm trajectories in the Cartesian space obtained from the motion tracking system by means of human-arm biomechanical models and sensor-fusion algorithms embedded in the Xsens technology. The desired pose of the robot is reconstructed taking into account the differences between the robot and human-arm kinematics and is obtained by suitably scaling to the human-arm link dimensions.

Configuration space control of KUKA Lightweight Robot LWR with EXARM Exoskeleton

Author  Telerobotics Lab

Video ID : 817

This video shows some advanced inverse kinematics mapping that enables the control of a redundant manipulator (KUKA LWR) by means of Cartesian location and geometric correspondence to the human arm. Thereby the null-space of the robot manipulator can be exploited to enable very intuitive operations. Joint limits and singularities are avoided, as well, by optimized mounting of the robot and the hand.

FlexIRob - Teaching null-space constraints in physical human-robot interaction

Author  AMARSi Consortium

Video ID : 818

The video presents an approach utilizing the physical interaction capabilities of compliant robots with data-driven and model-free learning in a coherent system in order to make fast reconfiguration of redundant robots feasible. Users with no particular robotics knowledge can perform this task in physical interaction with the compliant robot, for example, to reconfigure a work cell due to changes in the environment. For fast and efficient learning of the respective null-space constraints, a reservoir neural network is employed. It is embedded in the motion controller of the system, hence allowing for execution of arbitrary motions in task space. We describe the training, exploration, and the control architecture of the systems and present an evaluation of the KUKA Light-Weight Robot (LWR). The results show that the learned model solves the redundancy resolution problem under the given constraints with sufficient accuracy and generalizes to generate valid joint-space trajectories even in untrained areas of the workspace.

Visual servoing control of Baxter robot arms with obstacle avoidance using kinematic edundancy

Author  Chenguang Yang

Video ID : 819

Visual servoing control rby an obstacle avoidance strategy using kinematics redundancy has been developed and tested on a Baxter robot. A Point Grey Bumblebee2 stereo camera is used to obtain the 3-D point cloud of a target object. The object tracking task allocation between two arms has been developed by identifying workspaces of the dual arms and tracing the object location in a convex hull of the workspace. By employment of a simulated artificial robot as a parallel system as well as a task-switching weight factor, the robot is actually able to restore back to the natural pose smoothly in the absence of the obstacle. Two sets of experiments were carried out to demonstrate the effectiveness of the developed servoing control method.