A Control Method for Joint Torque Minimization of Redundant Manipulators Handling Large External Forces

© 2019, The Author(s). In this paper, a control method is developed for minimizing joint torque on a redundant manipulator where an external force acts on the end-effector. Using null space control, the redundant task is designed to minimize the torque required to oppose the external force, and reduce the dynamic torque. Furthermore, the joint motion can be weighted to factor in physical constraints such as joint limits, collision avoidance, etc. Conventional methods for joint torque minimization only consider the internal dynamics of the manipulator. If external forces acting on the end-effector are inadvertently implemented in to these control methods this could lead to joint configurations that amplify the resulting joint torque. The proposed control method is verified through two different case studies. The first case study involves simulation of high-pressure blasting. The second is a simulation of a manipulator lifting and moving a heavy object. The results show that the proposed control method reduces overall joint torque compared to conventional methods. Furthermore, the joint torque is minimized such that there is potential for a manipulator to execute certain tasks beyond its nominal payload capacity

Control of Manipulators on Moving Platforms Under Disturbance

University of Technology Sydney. Faculty of Engineering and Information Technology.Mobile robots, such as underwater vehicles, drones, and rovers, are now being combined with manipulators to perform a variety of work in the field. But current state of the art in control assumes that disturbances from the environment are minimal. However, the effects of wind, waves, and rough terrain may make it difficult for the vehicle to maintain a steady base for the manipulator. Or, in some cases, the vehicle may lack the control authority to negate disturbances in all directions. In this thesis, predictions of the base motion are used to formulate control strategies that enable a manipulator to proactively counter, and even make use of, these disturbances. Time series and Fourier series are commonly applied to many predictive control methods in literature. However, there are contradictory results in performance for different applications. To clarify these discrepancies, an objective comparison in prediction performance is made between time series, Fourier series, and Gaussian Process Regression (GPR) using motion data from underwater robots in waves. Analysis of the forecast errors and uncertainties show that GPR can produce better short-term. Furthermore, time series was found to be overconfident in the prediction, whereas Fourier series had the largest uncertainty. A predictive control method is then presented that enables a manipulator on a free-moving platform to maintain a steady end-effector pose. By using forecasts of the base motion, the manipulator can anticipate and negate this disturbance. Simulations and experiments are conducted, and it is shown that the proposed predictive control can reduce tracking error by 60% compared to a PID feedback controller. Moreover, kinematic constraints can be satisfied whilst simultaneously minimizing task error. A control strategy is also developed that allows a redundant manipulator to use the inertial forces produced by base disturbance to reduce joint torque. Further improvements are made by predicting changes in gravitational acceleration with respect to the manipulator. It is shown that joint torques can be reduced by 25% compared to a local minimization of the weighted torque norm. Lastly, a torque minimization method is presented for redundant manipulators handling large external forces. Most literature only addresses the internal dynamics. This thesis presents a method to minimize torque from both an external loading and the internal dynamics. This method can be applied to manipulators on moving platforms, and further enhanced by incorporating the base motion predictions

Self-motion control of kinematically redundant robot manipulators

Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 88-92)Text in English; Abstract: Turkish and Englishxvi,92 leavesRedundancy in general provides space for optimization in robotics. Redundancy can be defined as sensor/actuator redundancy or kinematic redundancy. The redundancy considered in this thesis is the kinematic redundancy where the total degrees-of-freedom of the robot is more than the total degrees-of-freedom required for the task to be executed. This provides infinite number of solutions to perform the same task, thus, various subtasks can be carried out during the main-task execution. This work utilizes the property of self-motion for kinematically redundant robot manipulators by designing the general subtask controller that controls the joint motion in the null-space of the Jacobian matrix. The general subtask controller is implemented for various subtasks in this thesis. Minimizing the total joint motion, singularity avoidance, posture optimization for static impact force objectives, which include maximizing/minimizing the static impact force magnitude, and static and moving obstacle (point to point) collision avoidance are the subtasks considered in this thesis. New control architecture is developed to accomplish both the main-task and the previously mentioned subtasks. In this architecture, objective function for each subtask is formed. Then, the gradient of the objective function is used in the subtask controller to execute subtask objective while tracking a given end-effector trajectory. The tracking of the end-effector is called main-task. The SCHUNK LWA4-Arm robot arm with seven degrees-of-freedom is developed first in SolidWorks® as a computer-aided-design (CAD) model. Then, the CAD model is converted to MATLAB® Simulink model using SimMechanics CAD translator to be used in the simulation tests of the controller. Kinematics and dynamics equations of the robot are derived to be used in the controllers. Simulation test results are presented for the kinematically redundant robot manipulator operating in 3D space carrying out the main-task and the selected subtasks for this study. The simulation test results indicate that the developed controller’s performance is successful for all the main-task and subtask objectives

Control of Redundant Flexible Manipulators with Redundancy Resolution

Author's accepted manuscript.© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper deals with the online control of a redundant flexible link manipulator to achieve minimum oscillations using the redundancy resolution technique. Different redundancy resolution techniques proposed and used for rigid link manipulators are tested for their use in the case of flexible link manipulators. The simulation model of a planar three-link flexible manipulator is used in this study. The redundancy resolution using kinetic energy minimization techniques is compared with the local joint acceleration minimization method to show the advantage of achieving minimum vibrations.acceptedVersio

A Stiffness-Adjustable Hyperredundant Manipulator Using a Variable Neutral-Line Mechanism for Minimally Invasive Surgery

In robotic single-port surgery, it is desirable for a manipulator to exhibit the property of variable stiffness. Small-port incisions may require both high flexibility of the manipulator for safety purposes, as well as high structural stiffness for operational precision and high payload capability. This paper presents a new hyperredundant tubular manipulator with a variable neutral-line mechanisms and adjustable stiffness. A unique asymmetric arrangement of the tendons and the links realizes both articulation of the manipulator and continuous stiffness modulation. This asymmetric motion of the manipulator is compensated by a novel actuation mechanism without affecting its structural stiffness. The paper describes the basic mechanics of the variable neutral-line manipulator, and its stiffness characteristics. Simulation and experimental results verify the performance of the proposed mechanism.Samsung Advanced Institute of Technolog

Modeling and Control of Flexible Link Manipulators

Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.publishedVersio

Ein hierarchisches Framework für physikalische Mensch-Roboter-Interaktion

Robots are becoming more than machines performing repetitive tasks behind safety fences, and are expected to perform multiple complex tasks and work together with a human. For that purpose, modern robots are commonly built with two main characteristics: a large number of joints to increase their versatility and the capability to feel the environment through torque/force sensors. Controlling such complex robots requires the development of sophisticated frameworks capable of handling multiple tasks. Various frameworks have been proposed in the last years to deal with the redundancy caused by a large number of joints. Those hierarchical frameworks prioritize the achievement of the main task with the whole robot capability, while secondary tasks are performed as well as the remaining mobility allows it. This methodology presents considerable drawbacks in applications requiring that the robot respects constraints imposed by, e.g., safety restrictions or physical limitations. One particular case is unilateral constraints imposed by, e.g., joint or workspace limits. To implement them, task hierarchical frameworks rely on the activation of repulsive potential fields when approaching the limit. The performance of the potential field depends on the configuration and speed of the robot. Additionally, speed limitation is commonly required in collaborative scenarios, but it has been insufficiently treated for torque-controlled robots. With the aim of controlling redundant robots in collaborative scenarios, this thesis proposes a framework that handles multiple tasks under multiple constraints. The robot’s reaction to physical interaction must be intuitive and safe for humans: The robot must not impose high forces on the human or react unexpectedly to external forces. The proposed framework uses novel methods to avoid exceeding position, velocity and acceleration limits in joint and Cartesian spaces. A comparative study is carried out between different redundancy resolution solvers to contrast the diverse approaches used to solve the redundancy problem. Widely used projector-based and quadratic programming-based hierarchical solvers were experimentally analyzed when reacting to external forces. Experiments were performed using an industrial redundant collaborative robot. Results demonstrate that the proposed method to handle unilateral constraints produces a safe and expected reaction in the presence of external forces exerted by humans. The robot does not exceed the given limits, while the tasks performed are prioritized hierarchically

TASK-BASED OPTIMIZATION OF MULTI-ARM SPACE ROBOTICS

There are many benefits to using multi-arm systems over a single arm system including higher flexibility in planning, better payload handling capacity, and reduction of joint torques. However, multi-arm systems are inherently more complex. This complexity does not necessarily translate to ``bigger" and ``heavier". This research seeks to answer the question of whether or not a multi-arm system can have lower mass than a single arm system. Using a task-based methodology, Independent single-arm and cooperative dual-arm manipulator systems are designed. A task defines the payload's motion and thus the manipulator's trajectory. Utilizing linear programming, a new method is developed in order to optimize the distribution of forces among the multiple arms in order to guarantee a minimum system mass. The mass of the motors and gears are estimated based on the required torque and speed, obtained from the trajectory and force-distribution. This study shows that a well-designed multi-arm system can in fact have a lower mass than a single-arm system. Further optimization demonstrates that a multi-arm system, when designed as a complete system rather than individual parts, can significantly reduce the total system mass

Modeling, Control and Estimation of Reconfigurable Cable Driven Parallel Robots

The motivation for this thesis was to develop a cable-driven parallel robot (CDPR) as part of a two-part robotic device for concrete 3D printing. This research addresses specific research questions in this domain, chiefly, to present advantages offered by the addition of kinematic redundancies to CDPRs. Due to the natural actuation redundancy present in a fully constrained CDPR, the addition of internal mobility offers complex challenges in modeling and control that are not often encountered in literature. This work presents a systematic analysis of modeling such kinematic redundancies through the application of reciprocal screw theory (RST) and Lie algebra while further introducing specific challenges and drawbacks presented by cable driven actuators. It further re-contextualizes well-known performance indices such as manipulability, wrench closure quality, and the available wrench set for application with reconfigurable CDPRs. The existence of both internal redundancy and static redundancy in the joint space offers a large subspace of valid solutions that can be condensed through the selection of appropriate objective priorities, constraints or cost functions. Traditional approaches to such redundancy resolution necessitate computationally expensive numerical optimization. The control of both kinematic and actuation redundancies requires cascaded control frameworks that cannot easily be applied towards real-time control. The selected cost functions for numerical optimization of rCDPRs can be globally (and sometimes locally) non-convex. In this work we present two applied examples of redundancy resolution control that are unique to rCDPRs. In the first example, we maximize the directional wrench ability at the end-effector while minimizing the joint torque requirement by utilizing the fitness of the available wrench set as a constraint over wrench feasibility. The second example focuses on directional stiffness maximization at the end-effector through a variable stiffness module (VSM) that partially decouples the tension and stiffness. The VSM introduces an additional degrees of freedom to the system in order to manipulate both reconfigurability and cable stiffness independently. The controllers in the above examples were designed with kinematic models, but most CDPRs are highly dynamic systems which can require challenging feedback control frameworks. An approach to real-time dynamic control was implemented in this thesis by incorporating a learning-based frameworks through deep reinforcement learning. Three approaches to rCDPR training were attempted utilizing model-free TD3 networks. Robustness and safety are critical features for robot development. One of the main causes of robot failure in CDPRs is due to cable breakage. This not only causes dangerous dynamic oscillations in the workspace, but also leads to total robot failure if the controllability (due to lack of cables) is lost. Fortunately, rCDPRs can be utilized towards failure tolerant control for task recovery. The kinematically redundant joints can be utilized to help recover the lost degrees of freedom due to cable failure. This work applies a Multi-Model Adaptive Estimation (MMAE) framework to enable online and automatic objective reprioritization and actuator retasking. The likelihood of cable failure(s) from the estimator informs the mixing of the control inputs from a bank of feedforward controllers. In traditional rigid body robots, safety procedures generally involve a standard emergency stop procedure such as actuator locking. Due to the flexibility of cable links, the dynamic oscillations of the end-effector due to cable failure must be actively dampened. This work incorporates a Linear Quadratic Regulator (LQR) based feedback stabilizer into the failure tolerant control framework that works to stabilize the non-linear system and dampen out these oscillations. This research contributes to a growing, but hitherto niche body of work in reconfigurable cable driven parallel manipulators. Some outcomes of the multiple engineering design, control and estimation challenges addressed in this research warrant further exploration and study that are beyond the scope of this thesis. This thesis concludes with a thorough discussion of the advantages and limitations of the presented work and avenues for further research that may be of interest to continuing scholars in the community

Energy-oriented Modeling And Control of Robotic Systems

This research focuses on the energy-oriented control of robotic systems using an ultracapacitor as the energy source. The primary objective is to simultaneously achieve the motion task objective and to increase energy efficiency through energy regeneration. To achieve this objective, three aims have been introduced and studied: brushless DC motors (BLDC) control by achieving optimum current in the motor, such that the motion task is achieved, and the energy consumption is minimized. A proof-ofconcept study to design a BLDC motor driver which has superiority compare to an off-the-shelf driver in terms of energy regeneration, and finally, the third aim is to develop a framework to study energy-oriented control in cooperative robots. The first aim is achieved by introducing an analytical solution which finds the optimal currents based on the desired torque generated by a virtual. Furthermore, it is shown that the well-known choice of a zero direct current component in the direct-quadrature frame is sub-optimal relative to our energy optimization objective. The second aim is achieved by introducing a novel BLDC motor driver, composed of three independent regenerative drives. To run the motor, the control law is obtained by specifying an outer-loop torque controller followed by minimization of power consumption via online constrained quadratic optimization. An experiment is conducted to assess the performance of the proposed concept against an off-the-shelf driver. It is shown that, in terms of energy regeneration and consumption, the developed driver has better performance, and a reduction of 15% energy consumption is achieved. v For the third aim, an impedance-based control scheme is introduced for cooperative manipulators grasping a rigid object. The position and orientation of the payload are to be maintained close to a desired trajectory, trading off tracking accuracy by low energy consumption and maintaining stability. To this end, an optimization problem is formulated using energy balance equations. The optimization finds the damping and stiffness gains of the impedance relation such that the energy consumption is minimized. Furthermore, L2 stability techniques are used to allow for time-varying damping and stiffness in the desired impedance. A numerical example is provided to demonstrate the results