Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network

The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinematic parameters of the robot in modules operational space reducing thus the computational time and facilitating implementation of advanced real-time feedback system for shape sensing. In the paper the method is applied for shape sensing and pose estimation of an articulated joint-based hyper-redundant robot with identical 2-DoF modules serially connected. Using a testing method based on HIL techniques the authors validate the computed kinematic model and the computed shape of the robot prototype. A second testing method is used to validate the end effector pose using an external sensory system. The experimental results obtained demonstrate the feasibility of using this type of sensor network and the effectiveness of the proposed shape sensing approach for hyper-redundant robots.

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.

Passive Decoupled Multi-Task Controller for Redundant Robots

Kinematic redundancy in robots makes it possible to execute several control tasks simultaneously. As some tasks are usually more important than others, it is reasonable to dynamically decouple them in order to ensure their execution in a hierarchical way or even without any interference at all. The most widely used technique is to decouple the system by feedback linearization. However, that requires to actively shape the inertia and consequently modify the natural dynamics of the robot. Here we propose a passivity-based multi-task tracking controller that preserves these inertial properties but fully compensates for task-space cross-couplings using external force feedback. Additionally, three formal proofs are provided: uniform exponential stability for trajectory tracking, passivity during physical interaction, and input-to-state-stability. The controller is validated in simulations and experiments and directly compared with the hierarchical PD+ approach and the feedback linearization. The proposed approach is well suited for safe physical human-robot interaction and dynamic trajectory tracking if measurements or estimations of the external forces are available.

Passive Decoupled Multi-Task Controller for Redundant Robots

Kinematic redundancy in robots makes it possible to execute several control tasks simultaneously. As some tasks are usually more important than others, it is reasonable to dynamically decouple them in order to ensure their execution in a hierarchical way or even without any interference at all. The most widely used technique is to decouple the system by feedback linearization. However, that requires to actively shape the inertia and consequently modify the natural dynamics of the robot. Here we propose a passivity-based multi-task tracking controller that preserves these inertial properties but fully compensates for task-space cross-couplings using external force feedback. Additionally, three formal proofs are provided: uniform exponential stability for trajectory tracking, passivity during physical interaction, and input-to-state-stability. The controller is validated in simulations and experiments and directly compared with the hierarchical PD+ approach and the feedback linearization. The proposed approach is well suited for safe physical human-robot interaction and dynamic trajectory tracking if measurements or estimations of the external forces are available.

Design and Validation of a Novel Cable-Driven Hyper-Redundant Robot Based on Decoupled Joints

In most of the prior designs of conventional cable-driven hyper-redundant robots, the multiple degree-of-freedom (DOF) bending motion usually has bending coupling effects. It means that the rotation output of each DOF is controlled by multiple pairs of cable inputs. The bending coupling effect will increase the complexity of the driving mechanism and the risk of slack in the driving cables. To address these problems, a novel 2-DOF decoupled joint is proposed by adjusting the axes distribution of the universal joints. Based on the decoupled joint, a 4-DOF hyper-redundant robot with two segments is developed. The kinematic model of the robot is established, and the workspace is analyzed. To simplify the driving mechanism, a kinematic fitting approach is presented for both proximal and distal segments and the mapping between the actuator space and the joint space is significantly simplified. It also leads to the simplification of the driving mechanism and the control system. Furthermore, the cable-driven hyper-redundant robot prototype with multiple decoupled joints is established. The experiments on the robot prototype verify the advantages of the design.

Design and Analysis of a Fully Actuated Cable-Driven Joint for Hyper-Redundant Robots with Optimal Cable Routing

Cable-driven hyper-redundant robots have been adopted in many fields for accessing harsh and confined environments that maybe inaccessible or dangerous for humans. The cable actuation strategy makes the robot hardware safer and increases the robot payload reducing its weight. In this paper, a novel design of a fully actuated cable-driven hyper-redundant robot has been proposed. This solution is a pulleyless design that decreases the mechanical complexity, allowing to reduce the robot arm diameter and avoid tension losses on the cables during the motion. Three different joint designs have been taken into account and experiments have been carried to study their performances. The kinematics for n-joint robot has been formulated and a cable routing optimization method based on genetic algorithm have been proposed and applied to a five-joints robot.