Christoph Stöger

Dynamic Model-based Control of Redundantly Actuated, Non-holonomnic, Omnidirectional Vehicles

Vehicles with several centered orientable wheels have one of the highest maneuverability and are hence an excellent choice for transportation tasks in narrow environments. However, they are non-holonomic, in general redundantly actuated, and additionally suffer from configuration singularities, which makes their modeling and control challenging. Existing control approaches only consider the vehicle kinematics whereas the required torques are commonly controlled by classical PD motor controllers. However, this leads to considerable tracking errors and a violation of the constraints especially during acceleration phases. Moreover, actuator counteractions and an undefined torque distribution can be observed. This paper introduces a model-based control concept that overcomes these issues. It resolves counteractions and distributes torques according to physical limitations which significantly reduces slippage and the energy consumption and further reduces the tracking error. To this end, an inverse dynamics solution of a redundantly parametrized model is used. The method is robust to configuration singularities. This is confirmed by experimental results.

Kinematic analysis and singularity robust path control of a non-holonomic mobile platform with several steerable driving wheels

The use of more than one steerable (standard) driving wheel allows a robot to perform omnidirectional motions. However, the modeling and control of such robots is challenging since the system is non-holonomic, nonlinear and typically over actuated. Moreover, such platforms exhibit kinematic singularities. A well known singular configuration is the configuration where two steerable driving wheels are coaxial aligned. This is highly problematic since this configuration corresponds to pure rotations, which is crucial for narrow space navigation. In this paper a control scheme with improved robustness w.r.t. these singularities is derived. It is based on the second order (accelerations) non-holonomic constraints. The remaining singularity is tackled by a regular parametrization of the robots motion. Thereupon a novel control concept is presented which is based on an input-output linearization in terms of a path parameter. The choice of this parametrization provides an additional parameter in the controller design. The approach is demonstrated for a prototype implementation.

A real-time nearly time-optimal point-to-point trajectory planning method using dynamic movement primitives

This paper focuses on highly efficient real-time capable time-optimal trajectory planning for point-to-point motions. A method based on the concept of dynamic movement primitives is developed. Thereby an offline generated time-optimal point-to-point trajectory considering nonlinear physical constraints serves as reference for a movement primitive. Through variation of the goal position in a small range around the reference target, new nearly time-optimal point-to-point trajectories are obtained. For the required reconsideration of the physical constraints, a strategy is derived from a common minimum-time optimization problem formulation. Finally a comparison between this and existing realtime capable time-optimal trajectory planning methods is drawn using a six degree-of-freedom serial robot.

Trajectory Tracking Control of a Quadcopter UAV Using Nonlinear Control

Recently trajectory tracking control of a quadcopter has been paid attention by academic and industry. This paper proposes two different strategies for trajectory tracking control of a quadcopter system implementing nonlinear control theory. The first approach is based on the integral backstepping technique, the second proposed one is an LQI (Linear Quadratic Integral) optimal controller with a feedback linearization so as to deal with the nonlinearity and the coupling components of the quadcopter state variables. The control laws for trajectory tracking using the proposed two strategies were validated by simulation and experimental results obtained from a quadcopter test bench. Simulation results show a comparison between the performance of each of the two control laws depending on the nonlinear model of the quadcopter system under investigation; the trajectory tracking has been achieved properly for different types of trajectories in presence of unknown disturbances. Simulation and practical results have shown coincided tracking with the command signals of the desired attitude. Superior tracking control has been exhibited with the proposed LQI optimal controller. It has been also noted that the proposed control approach exhibits an inherited decoupling control action, for which the control of one axis angle has relieved the dynamic coupling effect on the other two axes. Furthermore, intensive practical results have demonstrated the robustness of the proposed controller.

UKF-Assisted SLAM for 4WDDMR Localization and Mapping

Correct mobile robot localization requires precise knowledge of the robot’s pose in plane, i.e. the Cartesian x and y coordinates and yaw angle \( \theta \). Mobile robot pose information estimated from on-board odmetry sensors is not fully trusted and it suffers from unceratinties exerted by the robot incorporated with actuators nonlinearities and robot mechanical complexities which lead to a low degree of believe (DoB) of the robot localization. The present paper provides Unscented Kalman Filter (UKF) based approach assisted robot localization to provide trusted information with high DoB for the mobile robot’s pose. Particularly, estimating the current situation of the robot navigation system is complex due to the above mentioned phenomenons. An efficient and accurate estimation technique which applies probabilistic algorithm based UKF is proposed. The proposed technique is implemented and verified using MATLAB/SIMULINK®. Both practical and simulation results have demonstrated the vitality of the proposed estimation approach.

Parameter Identification and Model-Based Control of Redundantly Actuated, Non-holonomic, Omnidirectional Vehicles

Vehicles with centered orientable standard wheels are known to be omnidirectional and precise in their motion. The common decentralized strategy to control the driving velocities and wheel orientations leads to unnecessary high torques, an increased energy consumption as well as additional slippage due to the redundant actuation. This paper introduces a novel model-based control concept that overcomes these. It uses a minimal set of control variables within a PD control law to avoid counteractions. An additional inverse dynamics solution complements the control and further reduces slippage. The resulting generalized torque demand is optimal distributed among the drives. The paper additionally shows how the control performance can be further improved by an additional experiment which identify the inertia parameters of the vehicle. The overall approach is at the end validated by some experiments.

Modeling and Analysis of a Novel Passively Steered 4WD Mobile Platform Concept

Applications in the field of mobile robotics have high demands on flexibility and maneuverability of mobile platforms. Especially in logistics, vehicles have limited space for the movement. This paper presents the analysis and control of a mobile platform which uses a novel steering principle. The considered vehicle is able to perform a steered forward movement, lateral motion or pure rotation without the need of steering motors. The kinematics is analyzed and a kinematic model is derived. For simulation a dynamic model formulated in terms of redundant coordinates is used. A control scenario where reference values are commanded by a joystick is presented. For feedforward control design, a reduced dynamic model based on minimal velocities and the kinematic model are used. For feedback control, a cascaded structure with an inner velocity loop for the wheels and a superimposed steering control is used. The efficiency of the presented control approach is demonstrated by simulation results.

Dynamical Modeling and Swing-Up Control of a Self-balancing Cube

In this paper a balancing cube is presented. Driven flywheels are used as actuators for the balancing control. The cube is additionally equipped with an IMU measuring the orientation and rotational velocity of the cube. The control is done on an embedded control system. Based on the kinematical and dynamical modelling, two methods for swing-up of the cube are presented. The first one makes use of pre-defined trajectories, while for the second one a time/energy optimal solution subject to technological constraints is performed. Proportional control laws based on velocities and orientation measurements are used for stabilization. To demonstrate the effectiveness of the test bench, experimental results are shown.