Robot Excitation Trajectories for Dynamic Parameter Estimation using Optimized B-Splines

In this paper we adressed the problem of finding exciting trajectories for the identification of manipulator link inertia parameters. This can be formulated as a constraint nonlinear optimization problem. The new approach in the presented method is the parameterization of the trajectories with optimized B-splines. Experiments are carried out on a 7 joint Light-Weight robot with torque sensoring in each joint. Thus, unmodeled joint friction and noisy motor current measurements must not be taken into account. The estimated dynamic model is verified on a different validation trajectory. The results show a clear improvement of the estimated dynamic model compared to a CAD-valued model

A nonlinear disturbance observer for robotic manipulators

A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well

Integral Resonant Control for vibration damping and precise tip-positioning of a single-link flexible manipulator

Peer reviewedPostprin

On Sensorless Collision Detection and Measurement of External Forces in Presence of Modeling Inaccuracies

The field of human-robot interaction has garnered significant interest in the last decade. Every form of human-robot coexistence must guarantee the safety of the user. Safety in human-robot interaction is being vigorously studied, in areas such as collision avoidance, soft actuators, light-weight robots, computer vision techniques, soft tissue modeling, collision detection, etc. Despite the safety provisions, unwanted collisions can occur in case of system faults. In such cases, before post-collision strategies are triggered, it is imperative to effectively detect the collisions. Implementation of tactile sensors, vision systems, sonar and Lidar sensors, etc., allows for detection of collisions. However, due to the cost of such methods, more practical approaches are being investigated. A general goal remains to develop methods for fast detection of external contacts using minimal sensory information. Availability of position data and command torques in manipulators permits development of observer-based techniques to measure external forces/torques. The presence of disturbances and inaccuracies in the model of the robot presents challenges in the efficacy of observers in the context of collision detection. The purpose of this thesis is to develop methods that reduce the effects of modeling inaccuracies in external force/torque estimation and increase the efficacy of collision detection. It is comprised of the following four parts: 1. The KUKA Light-Weight Robot IV+ is commonly employed for research purposes. The regressor matrix, minimal inertial parameters and the friction model of this robot are identified and presented in detail. To develop the model, relative weight analysis is employed for identification. 2. Modeling inaccuracies and robot state approximation errors are considered simultaneously to develop model-based time-varying thresholds for collision detection. A metric is formulated to compare trajectories realizing the same task in terms of their collision detection and external force/torque estimation capabilities. A method for determining optimal trajectories with regards to accurate external force/torque estimation is also developed. 3. The effects of velocity on external force/torque estimation errors are studied with and without the use of joint force/torque sensors. Velocity-based thresholds are developed and implemented to improve collision detection. The results are compared with the collision detection module integrated in the KUKA Light-Weight Robot IV+. 4. An alternative joint-by-joint heuristic method is proposed to identify the effects of modeling inaccuracies on external force/torque estimation. Time-varying collision detection thresholds associated with the heuristic method are developed and compared with constant thresholds. In this work, the KUKA Light-Weight Robot IV+ is used for obtaining the experimental results. This robot is controlled via the Fast Research Interface and Visual C++ 2008. The experimental results confirm the efficacy of the proposed methodologies

Precise control of flexible manipulators

The design and experimental testing of end point position controllers for a very flexible one link lightweight manipulator are summarized. The latest upgraded version of the experimental set up, and the basic differences between conventional joint angle feedback and end point position feedback are described. A general procedure for application of modern control methods to the problem is outlined. The relationship between weighting parameters and the bandwidth and control stiffness of the resulting end point position closed loop system is shown. It is found that joint rate angle feedback in addition to the primary end point position sensor is essential for adequate disturbance rejection capability of the closed loop system. The use of a low order multivariable compensator design computer code; called Sandy is documented. A solution to the problem of control mode switching between position sensor sets is outlined. The proof of concept for endpoint position feedback for a one link flexible manipulator was demonstrated. The bandwidth obtained with the experimental end point position controller is about twice as fast as the beam's first natural cantilevered frequency, and comes within a factor of four of the absolute physical speed limit imposed by the wave propagation time of the beam

Topics in Machining with Industrial Robot Manipulators and Optimal Motion Control

Two main topics are considered in this thesis: Machining with industrial robot manipulators and optimal motion control of robots and vehicles. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of the strong process forces required for the task. Because of the process forces, the nonlinear dynamics of the manipulator, such as the joint compliance and backlash, may significantly degrade the achieved machining accuracy of the manufactured part. In this thesis, a macro/micro-manipulator configuration is considered to the purpose of increasing the milling accuracy. In particular, a model-based control architecture is developed for control of the macro/micro-manipulator setup. The considered approach is validated by experimental results from extensive milling experiments in aluminium and steel. Related to the problem of high-accuracy milling is the topic of robot modeling. To this purpose, two different approaches are considered; modeling of the quasi-static joint dynamics and dynamic compliance modeling. The first problem is approached by an identification method for determining the joint stiffness and backlash. The second problem is approached by using gray-box identification based on subspace-identification methods. Both identification algorithms are evaluated experimentally. Finally, online state estimation is considered as a means to determine the workspace position and orientation of the robot tool. Kalman Filters and Rao-Blackwellized Particle Filters are employed to the purpose of sensor fusion of internal robot measurements and measurements from an inertial measurement unit for estimation of the desired states. The approaches considered are fully implemented and evaluated on experimental data. The second part of the thesis discusses optimal motion control applied to robot manipulators and road vehicles. A control architecture for online control of a robot manipulator in high-performance path tracking is developed, and the architecture is evaluated in extensive simulations. The main characteristic of the control strategy is that it combines coordinated feedback control along both the tangential and transversal directions of the path; this separation is achieved in the framework of natural coordinates. One motivation for research on optimal control of road vehicles in time-critical maneuvers is the desire to develop improved vehicle-safety systems. In this thesis, a method for solving optimal maneuvering problems using nonlinear optimization is discussed. More specifically, vehicle and tire modeling and the optimization formulations required to get useful solutions to these problems are investigated. The considered method is evaluated on different combinations of chassis and tire models, in maneuvers under different road conditions, and for investigation of optimal maneuvers in systems for electronic stability control. The obtained optimization results in simulations are evaluated and compared

Model-Based Robot Control and Multiprocessor Implementation

Model-based control of robot manipulators has been gaining momentum in recent years. Unfortunately there are very few experimental validations to accompany simulation results and as such majority of conclusions drawn lack the credibility associated with the real control implementation

An Overview of Kinematic and Calibration Models Using Internal/External Sensors or Constraints to Improve the Behavior of Spatial Parallel Mechanisms

This paper presents an overview of the literature on kinematic and calibration models of parallel mechanisms, the influence of sensors in the mechanism accuracy and parallel mechanisms used as sensors. The most relevant classifications to obtain and solve kinematic models and to identify geometric and non-geometric parameters in the calibration of parallel robots are discussed, examining the advantages and disadvantages of each method, presenting new trends and identifying unsolved problems. This overview tries to answer and show the solutions developed by the most up-to-date research to some of the most frequent questions that appear in the modelling of a parallel mechanism, such as how to measure, the number of sensors and necessary configurations, the type and influence of errors or the number of necessary parameters