Frese, Udo
Lade...
Preferred name
Frese, Udo
Official Name
Frese, Udo
3 Ergebnisse
Gerade angezeigt 1 - 3 von 3
- Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Dynamic Bat-Control of a Redundant Ball Playing Robot(2017-02-02); ; ; This thesis shows a control algorithm for coping with a ball batting task for an entertainment robot. The robot is a three jointed robot with a redundant degree of freedom and its name is "Doggy". Doggy because of its dog-like costume. Design, mechanics and electronics were developed by us. DC-motors control the tooth belt driven joints, resulting in elasticities between the motor and link. Redundancy and elasticity have to be taken into account by our developed controller and are demanding control tasks. In this thesis we show the structure of the ball playing robot and how this structure can be described as a model. We distinguish two models: One model that includes a flexible bearing, the other does not. Both models are calibrated using the toolkit Sparse Least Squares on Manifolds (SLOM) - i.e. the parameters for the model are determined. Both calibrated models are compared to measurements of the real system. The model with the flexible bearing is used to implement a state estimator - based on a Kalman filter - on a microcontroller. This ensures real time estimation of the robot states. The estimated states are also compared with the measurements and are assessed. The estimated states represent the measurements well. In the core of this work we develop a Task Level Optimal Controller (TLOC), a model-predictive optimal controller based on the principles of a Linear Quadratic Regulator (LQR). We aim to play a ball back to an opponent precisely. We show how this task of playing a ball at a desired time with a desired velocity at a desired position can be embedded into the LQR principle. We use cost functions for the task description. In simulations, we show the functionality of the control concept, which consists of a linear part (on a microcontroller) and a nonlinear part (PC software). The linear part uses feedback gains which are calculated by the nonlinear part. The concept of the ball batting controller with precalculated feedback gains is evaluated on the robot. This shows successful batting motions. The entertainment aspect has been tested on the Open Campus Day at the University of Bremen and is summarized here shortly. Likewise, a jointly developed audience interaction by recognition of distinctive sounds is summarized herein. In this thesis we answer the question, if it is possible to define a rebound task for our robot within a controller and show the necessary steps for this.Dissertation425 203 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, NAO greift - Explorieren und Greifen unbekannter Objekte auf einem performanzlimitierten humanoiden Roboter mit Hilfe vorberechneter Tabellen(2016-02-09); ; ; Why can't I buy a flower watering robot? No unusual question considering that there are already affordable vacuum cleaner and lawn mower robots available. Thus the next questions are, what requirements must be met by a flower watering robot and does it take a high-priced research robot to do it? As the activity of flower watering contains a variety of difficult tasks this work is concentrated on the intermediate step of autonomously exploring, detecting and grasping an unknown object such as a watering can. In particular, an overall system is introduced that enables this functionality for the performance-limited humanoid robot NAO. Furthermore, the presented system operates online and thus without external computation at runtime. In order to increase the system performance several precomputed tables containing the workspaces of different body parts are used. Moreover, the precomputed workspace constitutes as a central element as it is not only used for motion planning but also for the viewpoint planning. Furthermore, the workspace provides a connection between the very limited degrees of freedom and the need of mobility in reality.Dissertation476 230 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Inertial Motion Capturing : Rigid Body Pose and Posture Estimation with Inertial Sensors(2017-02-03); ; ; This dissertation is about estimating poses from inertial sensor data, that is estimating orientations and positions. Both poses of single rigid bodies as well as poses of so called skeletons, i.e. systems of jointed rigid bodies, are covered. The key insight into orientation estimation of a single rigid body is to view it as the fusion of sensor data and its dynamics model with prior information. To this end, three different Kalman Filter variations are presented, which fuse the same sensor data and the same dynamics with three different priors. It turns out that the classical model to correct the inclination in an orientation estimator, namely comparing the accelerometer measurement with (negative) gravity, is equivalent to the assumption that the rigid body does not accelerate on long-term average. Assuming that the velocity is zero on long-term average or that the rigid body stays at the same position on long-term average are alternative assumptions and both priors also yield orientation estimators. Moreover, the orientation estimator resulting from the position assumption also estimates a position, which is locally accurate - it follows the accelerometer measurements - but does not drift unboundedly, which it would if the position were obtained by integrating according to the dynamic model only. The focus here is more on the interplay of inertial sensor data and its dynamic model with prior information than it is on practical applications. For instance, for the integrated position to be a usable quantity, the estimate has to be conditioned on the long-term average of the position being zero instead of the velocity or acceleration being zero. In the second, bigger part of this dissertation the posture of a skeleton, i.e. the poses of all the skeleton's bodies, are estimated, again using inertial sensor data only. Notably, no magnetometers are used to recover the rotations around the vertical. Without magnetometers, the rotation of the skeleton as a whole around the vertical, of course, can not be estimated. However, to asses the skeleton's posture, it is also not important. If inertial sensor data of all bodies is fused with the prior information that a skeleton's bodies are jointed using hinges and spherical joints, the relative orientations of the bodies become observable completely: If two accelerometers of two jointed bodies measure the acceleration of a motion, then the relative orientation of those two bodies can be recovered from the directions of the accelerometer measurements, if effects due to movements of the joints are compensated for. The posture estimator that exploits this insight is developed and used in the sensor suit SIRKA, which is workwear with inertial sensors embedded into the clothing. On computationally very limited hardware, which is completely integrated into the suit, the estimator yields posture estimates in real-time. To make this possible, a technique to decouple the sensor's sampling rate from the estimation rate is introduced. Moreover, the sensor orientations and positions inside the suit are almost arbitrary and do not need adjustment. Instead, they are calibrated automatically. The motion capturing workwear is used in a real-world setting, estimating the posture of a worker welding steel on a shipyard. That would not be possible using a motion capturing suit relying on magnetometers.Dissertation819 232