Past studies have shown that ontogenetic treatment of quinpirole (QNP) produces a number of behavioral effects that can be alleviated by administration of antipsychotics such as haloperidol, providing a useful behavioral screen for disorders such as schizophrenia. In this study, 16 female Sprague-dawley rats were used, with 8 rats injected with QNP(1 mg/kg) and 8 rats injected with saline once daily from postnatal days (PD) 1-11. All rats were behaviorally tested as adults on several tasks: The reference and working memory versions of the Morris water task (MWT), the radial arm maze (RAM), the Whishaw reaching task, and locomotor activity. Results showed that on the MWT, QNP-treated rats demonstrated significant enhancement on acquisition latency of both versions, but a deficit on the probe trial of the reference memory version. The acquisition enhancement was due to hyperlocomotion observed in QNP-treated rats, because these animals demonstrated increased locomotion in an activity chamber compared to controls. On the RAM, QNP-treated rats demonstrated a deficit in reference memory but not working memory, congruent with MWT findings. Interestingly, QNP-treated rats demonstrated a significant enhancement in reaching accuracy on the Whishaw reaching task, which may due to an overactive dopaminergic system. Future studies will analyze underlying mechanisms.

Robots have an underlying model to control their joints with the aim of reaching a specific pose. The accuracy of a robot is based on the underlying model and its parameters. The parameters of the underlying model of a robot are based on the ideal geometry and set by the manufacturer. If the parameters do not represent the physical robot accurately, the movements of the robot become inaccurate. Methods to optimize the parameters to represent the physical robot more accurately exist and result in an accuracy enhancement. Nevertheless, the underlying model of the manufacturer remains of analytical form and therefore has a limited complexity which hinders the model to represent arbitrary non-linearities and higher degree relations. To further enhance the accuracy of a robot by using a model with a higher complexity, this work investigates the use of a model of the inverse kinematics based on Artificial Intelligence (AI). The accuracy is investigated for a robot with an attached tool. In a first step, the development and initial evaluation of a suitable AI model is conducted in a simulated environment. Afterwards, the uncompensated accuracy of the robot with the tool is assessed and measurements are recorded. Using the measurements, an AI model based on the measurements of physical robot. The model is evaluated on the physical robot with a tool to quantify the achieved accuracy enhancement.

Precision control of translational motion is vital for many CNC machine tools as the motion of the machinery affects the dimensional tolerance of the manufactured goods. However, the direct measurement along with the accurate motion control of machine usually requires relatively expensive sensors i.e. potentiometers, linear scales, laser interferometers. Hence, this study attempts to develop reference models utilizing low-cost sensors (i.e. rotary encoders) for accurate position estimation. First, an indirect measurement performance is investigated on a Timing Belt driven carriage by a DC Motor with a backlash included Gearbox head. An advanced interpolated technique is proposed to compensate the position errors while using indirect measurement to reduce the total cost. Then, a similar study was realized with a ball screw driven system. Next, a cable drum driven measurement technique is proposed to the machines which have long travel distance like plasma cutters. A test setup is proposed and manufactured to investigate the capstan drive systems. Finally, characteristics of Optical Mouse Sensors are investigated from different point of views and a test setup is proposed and manufactured to evaluate their performances in long terms. Beside all of these parts, motion control algorithms and motion control integrated circuits are designed and manufactured to realize experimental studies in a detailed manner.