Model-based Motion Control Research Articles

System and Experiments of Model-Driven Motion Planning and Control for Autonomous Vehicles

This article presents a model-based motion planning and control system for autonomous vehicles and its experimental validation. The system consists of four modules: 1) global routing; 2) behavior planner; 3) local trajectory generation; and 4) trajectory tracking. The algorithm and software of each module are detailed, including a behavior planner with unified models to handle typical scenarios in both highway and urban driving, a deterministic sampling algorithm for robust responsive trajectory generation, and a dynamics-and-delay-aware preview algorithm to achieve accurate trajectory tracking. The developed system is implemented and tested at the Mcity test facility with a full-size automated car and a dozen of challenging traffic scenarios.

Review of Electronics-Free Robotics: Toward a Highly Decentralized Control Architecture

In recent years, conventional model-based motion control has become more challenging owing to the continuously increasing complexity of areas in which robots must operate and navigate. A promising approach for solving this issue is by employing interaction-based robotics, which includes behavior-based robotics, morphological computations, and soft robotics that generate control and computation functions based on interactions between the robot body and environment. These control strategies, which incorporate the diverse dynamics of the environment to generate control and computation functions, may alleviate the limitations imposed by the finite physical and computational resources of conventional robots. However, current interaction-based robots can only perform a limited number of actions compared with conventional robots. To increase the diversity of behaviors generated from body–environment interactions, a robotic body design methodology that can generate appropriate behaviors depending on the various situations and environmental stimuli that arise from them is necessitated. Electronics-free robotics is reviewed herein as a paradigm for designing robots with control and computing functions in each part of the body. In electronics-free robotics, instead of using electrical sensors or computers, a control system is constructed based on only mechanical or chemical reactions. Robotic bodies fabricated using this approach do not require bulky electrical wiring or peripheral circuits and can perform control and computational functions by obtaining energy from a central source. Therefore, by distributing these electronics-free controllers throughout the body, we hope to design autonomous and highly decentralized robotic bodies than can generate various behaviors in response to environmental stimuli. This new paradigm of designing and controlling robot bodies can enable realization of completely electronics-free robots as well as expand the range of conventional electronics-based robot designs.

Dynamic modeling and experimental analysis of an underwater glider in the ocean

An accurately dynamic model is crucial for systematic model-based motion prediction, control, and optimization. Historical dynamic models for underwater gliders ignored the ocean influence. This paper proposes dynamic modeling and experimental analysis of an underwater glider in the ocean. The physics-based dynamic model of the underwater glider is established first based on the Lagrangian equation, including gravity and buoyancy effects, the couplings caused by adjustment buoyancy and moving internal masses, and hydrodynamics caused by the fluid environment. Then, the compensation models of the underwater glider in the ocean are constructed to capture the critical effects on the underwater glider motion, including models of hydrological based on deep neural network, buoyancy loss based on finite element analysis, and ocean currents. Finally, field experiments and simulation studies demonstrate the effectiveness and accuracy of the proposed method.

Flexible-Link Multibody System Eigenvalue Analysis Parameterized with Respect to Rigid-Body Motion

The dynamics of flexible multibody systems (FMBSs) is governed by ordinary differential equations or differential-algebraic equations, depending on the modeling approach chosen. In both the cases, the resulting models are highly nonlinear. Thus, they are not directly suitable for the application of the modal analysis and the development of modal models, which are very useful for several advanced engineering techniques (e.g., motion planning, control, and stability analysis of flexible multibody systems). To define and solve an eigenvalue problem for FMBSs, the system dynamics has to be linearized about a selected configuration. However, as modal parameters vary nonlinearly with the system configuration, they should be recomputed for each change of the operating point. This procedure is computationally demanding. Additionally, it does not provide any numerical or analytical correlation between the eigenpairs computed in the different operating points. This paper discusses a parametric modal analysis approach for FMBSs, which allows to derive an analytical polynomial expression for the eigenpairs as function of the system configuration, by solving a single eigenvalue problem and using only matrix operations. The availability of a similar modal model, which explicitly depends on the system configuration, can be very helpful for, e.g., model-based motion planning and control strategies towards to zero residual vibration employing the system modal characteristics. Moreover, it allows for an easy sensitivity analysis of modal characteristics to parameter uncertainties. After the theoretical development, the method is applied and validated on a flexible multibody system, specifically using the Equivalent Rigid Link System dynamic formulation. Finally, numerical results are presented and discussed.

Model-based motion control for underwater vehicle-manipulator systems with one of the three types of servo subsystems

This paper deals with a motion control scheme for underwater robots equipped with manipulators. In general, for each robot, its manipulator is directly driven by electric motors with position sensors such as encoders, whereas its robot body is propelled by marine thrusters with position sensors such as inertial measurement units. It has been pointed out in the literature that for this type of underwater robots, its robot body control is more challenging than its manipulator control, because the robot body has much larger inertia, and many more inaccurate position sensors and actuators than the manipulator. Therefore, it may be practically difficult to accurately control the motion of the robot body, even if an advanced control scheme with good performance is implemented in the controller of the robot body. In this paper, we develop a model-based motion controller for the manipulator under the condition that the robot body is independently controlled by a motion controller with poor performance. Its features are to design the manipulator controller in consideration of the dynamics of the robot body including the marine thrusters as well as those of the manipulator, and to be applicable to underwater robots equipped with one of the three types of servo systems (i.e., a voltage-controlled, a torque-controlled, and a velocity-controlled servo system). Some stability properties of the control system were theoretically ensured in the stability analysis. Furthermore, these results were supported by those obtained in numerical simulations.

A Dynamic Parameter Identification Method for Flexible Joints Based on Adaptive Control

This paper investigates the dynamic parameter identification for flexible joints without additional sensors. The estimation accuracy of traditional methods based on the original dynamic model is limited by measurement of angular acceleration. Recently, approaches using integral operations are raised to solve this problem. However, the integral operations easily result in error accumulation and deteriorate the parameter estimation accuracy. This study proposes a new dynamic parameter identification method for flexible joints. By constructing an alternative system function and estimating its outputs through nonmodel-based adaptive control, we avoid the measurement of angular acceleration and integral operations. On this basis, dynamic parameters of flexible joints are estimated using the recursive least squares (RLS) method. The experimental results indicate that the proposed method possesses better estimation accuracy than the general RLS- and integral-based methods. It is also validated that the proposed method can provide accurate estimation even under a relatively low-resolution system. Applications to model-based motion control and physical human-robot interaction are also verified.

A Method to Identify the Nonlinear Stiffness Characteristics of an Elastic Continuum Mechanism

The humanoid robot David is equipped with a novel robotic neck based on an elastic continuum mechanism (ECM). To realize a model-based motion control, the six dimensional stiffness characteristics needs to be known. This letter presents an approach to experimentally identify the stiffness characteristic using a robot manipulator to deflect the ECM and measure the Cartesian wrenches and Cartesian poses with external sensors. A three-step process is proposed to establish Cartesian wrench and pose pairs experimentally. The process consists of a simulation step, to select a good model, a second step that extracts effective poses from workspace which are sampled experimentally and the third step, the pose sampling procedure in which the robot drives the ECM to these effective poses. A full cubic polynomial regression model is adopted based on simulation data to fit the stiffness characteristics. To extract the poses to be sampled in the experiments, two different approaches are evaluated and compared to ensure a well-posed identification. The identification process on the hardware is performed by using Cartesian impedance and inverse kinematics control in combination to comply with the physical constraints imposed by the ECM.

Integrated Torque Vectoring Control for a Three-Axle Electric Bus Based on Holistic Cornering Control Method

An integrated chassis control framework that consists of a basic chassis controller and a torque vectoring controller is designed for a three-axle electric bus with distributed motor-driven and active rear steering subsystems. In the basic chassis controller, the active speed limiting control is integrated for antisideslip and antirollover purposes, and the interaxle torque distribution ratio is optimized for energy economy. Meanwhile, the active rear steering control is designed for the tire-wear coordinating purpose. In the torque vectoring controller, the model-based motion control algorithm based on the holistic cornering control method is designed, by which a torque increment is generated at each wheel to change the plane motion states of the vehicle. To solve the optimal torque increment vector, a real-time constrained quadratic programming problem is formulated. The constraints related to the wheel torque limits, the tire friction limits, and the anti-wheel-slip requirements are constructed and converted as the upper and lower bounds of the increments of the longitudinal tire forces. To verify the performance of the control framework, a Trucksim-Simulink cooperative test platform is established. The test results show satisfactory performances on energy economy, anti-wheel-slip, and the safety and stability of the motion control.

A Bio-inspired Soft Robotic Arm: Kinematic Modeling and Hydrodynamic Experiments

Soft robotics has several promising properties for aquatic applications, such as safe interaction with environments, lightweight, low cost, etc. In this paper, we proposed the kinematic modeling and hydrodynamics experiments of a soft robotic arm with 3D locomotion capacity. We developed a mathematical model that incorporates the angle correction, as well as the open-loop model-based motion control. The model could precisely predict the three-dimensional (3D) movement, and the location error is less than 5.7 mm in different attitudes. Furthermore, we performed the hydrodynamic investigations and simultaneously measured the hydrodynamic forces and the wake flows at different amplitudes (50 mm, 100 mm, 150 mm, 200 mm) and frequencies (0.3 Hz, 0.4 Hz, 0.5 Hz) of the soft arm. Surprisingly, we found that the magnitudes of the hydrodynamic force (<1 N) and the torques (<0.08 N·m) of dynamically moving soft arm were tiny, which leads to negligible inertial effect for the underwater vehicle than those of the traditional rigid underwater manipulator. Finally, we demonstrated underwater picking and placing tasks of the soft manipulator by using a computer program that controls the tip attitude and velocity. This study may inspire future underwater manipulators that have properties of low-inertial, low power cost and can safely interact with the aquatic environments.

Identification of System Dynamics with Time Delay: a Two-Stage Frequency Domain Approach

Frequency domain identification of system parameters and time delay is essential for model-based motion control of dynamic systems. Conventional approaches incorporate the delay into the model through an explicit model parametrization, which results in a high amount of nonlocal minima. In this paper, a new strategy is proposed based on a two-stage frequency domain approach to linearly incorporate the delay in the parameter vector of the system. This enables the proposed method to accurately identify both the time delay and system parameters. In a first stage, the system is parametrized and the delay is approximated using rational (all-pass) orthonormal basis functions. The resulting constraints on the individual delay approximation parameters are relaxed through a general all-pass constraint which is enforced iteratively by reformulating the identification algorithm. In a second stage, the continuous time delay term is identified in a convex problem with fixed system parameters using the previous approximates as starting values. Finally, simulations and experimental results validate the effectiveness of this new two-stage method.

Stabilization of Internal Dynamics of Underactuated Systems by Periodic Servo-Constraints

The model-based motion control of underactuated, multiple degree-of-freedom, complex multibody systems is in focus. Underactuated mechanical systems possess less number of independent control inputs than degrees-of-freedom. The main difficulty in their control is caused by the dynamics of the uncontrolled part of the system. The complexity of multibody systems makes the dynamical and control formulation difficult. The direct application of traditional control techniques available in the literature can lead to unstable dynamic behavior in many cases. In order to avoid instability, these general methods are usually adapted for specific problems in an intuitive way. Here, we present a direct, more algorithmic approach, and propose the use of periodic servo-constraints to overcome stability problems and enhance the dynamic behavior. An exact, stability analysis-based method is also proposed for tuning the control parameters. A stability analysis procedure is developed which is directly applicable for investigating the dynamics of mechanical systems described by dependent coordinates and mathematically formulated as a set of algebraic differential equations.

Model-based motion control for multi-axis servohydraulic shaking tables

The shaking table is an essential testing tool in the development of earthquake resistant buildings and infrastructure, so improving its performance is an important contribution to saving lives. Currently the bandwidth and accuracy of shaking tables is such that earthquake motion often cannot be replicated with the desired fidelity. A new model-based motion control method is presented for multi-axis shaking tables. The ability of this method to decouple the control axes is demonstrated. A linear parameter varying modal control approach is used – i.e. the modes of vibration of the system are controlled individually, with the modal decomposition repeated at each time step to account for parameter variations. For each mode, a partial non-linear dynamic inversion is performed in the control loop. Feedback is based on a combination of position and acceleration measurements. A command feedforward method is proposed to increase the tracking bandwidth, thus the controller has a two degree-of-freedom structure. Experimental and simulation results are presented for a large (43t total) six degree-of-freedom shaking table. The simulation results are based on a detailed, validated model of the table. Experimental results show that the controller gives exceptional performance compared a conventional proportional controller: for example the horizontal acceleration bandwidth is six-times higher at over 100Hz, which is also many times higher than the hydraulic resonant frequency. These results will allow a step change in earthquake simulation accuracy.

Motion control of industrial robots by considering serial two-link robot arm model with joint nonlinearities

This paper presents a model based motion control approach for industrial robots by considering a serial two-link robot arm model with joint nonlinearities. In order to achieve the desired performance using the model based control approaches, it is important to obtain relevant models of both kinematics and dynamics including nonlinear characteristics. Main nonlinear components that lead to trajectory tracking errors of typical multi-axis industrial robot are joint nonlinearities in each axis and dynamic coupling effects between different axes. In this paper, a parametric modeling approach is introduced to reproduce behaviors of a serial two-link robot arm with joint nonlinearities. Nonlinear stiffness, angular transmission errors, and friction in these two links are directly identified as joint nonlinearities. This approach is applied for the serial two-link arm of a typical multi-axis industrial robot, which has low frequency vibration modes and significantly affects to the trajectory performance. Effectiveness of the modeling is verified by comparative studies with numerical simulations and experiments. Finally, a 2-DOF control scheme with the identified two-link dynamic model and a feedback loop-shaping with a variable notch filter are applied to improve the performance of trajectory tracking and residual vibration suppression.

Integration for the next generation

In this paper, the interaction control schemes suitable for implementation on industrial robot units are presented. In particular, the focus is on impedance control and parallel control, which are conceived to manage the interaction with a more or less compliant environment without requiring an accurate model thereof. All the considered schemes are based on an inner motion control loop, which can be the usual independent joint control of PID type or an advanced model-based motion control law with superior tracking performance. The inner motion control loop is in charge of tracking the reference trajectory computed by the outer interaction control loop. Special emphasis is given to controlling 6-degrees-of-freedom (DOF) interaction tasks involving the end-effector position and orientation when a contact force and moment are applied.

Kinematic and dynamic modelling for real-time control of Tau parallel robot

This paper presents the methodology of the kinematic and dynamic modeling for a newly developed parallel robot with the so-called Tau configuration. A set of analytical kinematic solutions has been developed for this parallel structure. A rigid body dynamic model has been formulated based on the principle of virtual work. Specific requirements including model term separation for real-time model based motion control are addressed in the analytical solutions, which are verified by both numerical simulation and actual experiments. This analytical approach enables the real-time control of this parallel robot with high positioning accuracy.

Neuro-fuzzy and model-based motion control for mobile manipulator among dynamic obstacles

This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.

Model-Based Motion and Force Control for Flexible-Joint Robot Manipulators

Two model-based control algorithms to control the motion and force of flexible-joint robot manipulators are presented. Both algorithms are based on the feedback-linearization concept, and utilize a fourth-order feedback-linearizable model of the flexible-joint manipulators. The first algorithm, dynamic hy brid controller, deals with the problem where the flexible-joint robot is constrained by a rigid environment, and aims at di rect control of the contact forces. A constraint frame is derived that enables decoupling of the system into a position subsystem and a force subsystem. A nonlinear feedback-control law is designed to first decouple and linearize the constrained flexible- joint manipulator system, then impose desired closed-loop characteristics in each subsystem independently. The second algorithm, impedance controller, aims at regulating the rela tionship between the contact force and the difference between the commanded and true positions of the end point. A desired target impedance is designed for the end point of the flexible- joint robot manipulator in the reference frame. A nonlinear feedback controller is designed to linearize the system and to impose the target impedance. The same controller is used when the robot is performing compliant and free motions. An experimental two-link, flexible-joint robot manipulator in con tact with a straight wall is used to evaluate and compare the performance of the two controllers.