There are several types of singularities in controlling robotic manipulators: kinematic singularity, algorithmic singularity, semi-kinematic singularity, semi-algorithmic singularity, and representation singularity. The kinematic and algorithmic singularities have been investigated intensively because they are not predictable or difficult to avoid. The problem with these singularities is an unnecessary performance reduction in non-singular region and the difficulty in performance tuning. Tn this paper, we propose a method of avoiding kinematic and algorithmic singularities by applying a task reconstruction approach while maximizing the task performance by calculating singularity measures. The proposed method is implemented by removing the component approaching the singularity calculated by using singularity measure in real time. The outstanding feature of the proposed task reconstruction method (TR-method) is that it is based on a local task reconstruction as opposed to the local joint reconstruction of many other approaches. And, this method has dynamic task priority assignment feature which ensures the system stability under singular regions owing to the change of task priority. The TR-method enables us to increase the task controller gain to improve the task performance whereas this increase can destabilize the system for the conventional algorithms in real experiments. In addition, the physical meaning of tuning parameters is very straightforward. Hence, we can maximize task performance even near the singular region while simultaneously obtaining the singularity-free motion. The advantage of the proposed method is experimentally tested by using the 7-dof spatial manipulator, and the result shows that the new method improves the performance several times over the existing algorithms.

This paper deals with motion planning algorithm for kinematically redundant manipulators that are not fixed to the ground. Differently from usual redundant manipulators fixed to the ground, the stability issue should be taken into account to prevent the robot from falling down. The typical ZMP equation, which is employed in human walking, will be employed to evaluate the stability. This work proposes a feed forward ZMP planning algorithm. The algorithm embeds the 'ZMP equations' indirectly into the kinematics of the kinematic model of a manipulator via a ZMP stability index The kinematic self motion of the redundant manipulator drives the system in such a way to keep or plan the ZHP at the desired position of the footprint. A sequential redundancy resolution algorithm exploiting the remaining kinematic redundancy is also proposed to enhance the performances of joint limit index and manipulability. In addition, the case exerted by external forces is taken into account. Through simulation for a 5 DOF redundant robot model, feasibility of the proposed algorithms is verified. Lastly, usual applications of the proposed kinematic model are discussed.

Uncertainties are inevitable in robotic assembly in unstructured environment since it is difficult to construct fixtures to guide motions of robots. This paper proposes an augmented Petri net and an algorithm to adapt the assembly model on-line during actual assembly process. The augmented Petri net identifies events using force and position information simultaneously. Unmodeled contact states are identified and incorporated into the model on-line. The proposed method increases the level of intelligence of the robot system by enhancing the autonomy. The proposed method is evaluated by simulation and experiments with L-type peg-in-hole assembly using a two-arm robot system.

In this paper a mathematical framework fur deriving acceleration bounds from given joint torque limits of multiple cooperating robots are described. Especially when the different frictional contacts for every contact are assumed and the torque limits are given in 2-norm sense, we show that the resultant geometrical configuration for the acceleration is composed of corresponding parts of ellipsoids. Since the frictional forces at the contacts are proportional to the normal squeezing forces, the key points of the work includes how to determine internal forces exerted by each robot in order not to cause slip at the contacts while the object is carried by external forces. A set of examples composed of two robot systems are shown with point-contact-with-friction model and insufficient or proper degree of freedom robots.

In this paper, fault tolerant algorithm is presented for a servo manipulator system. For fault tolerance of a servo manipulator system, reconfiguration algorithm accommodating a motor's failure has been presented. The algorithm considers a transport's degree of freedoms as redundant joints of a servo manipulator. The reconfiguration algorithm recovers the end effector's motion in spite of one motor's failure A modified pseudo inverse redistribution method has been proposed for the reconfiguration algorithm. Numerical examples and hardware tests have been presented to verify the proposed methods.

In this paper, we present a reduced-order observer for a class of nonlinear systems based on the input output linearization. While the most results in the literature presented full-order nonlinear observer, we proposed a procedure for the design of reduced-order observer far nonlinear systems that are not necessarily observable. Assuming that there exists a global observer fer internal dynamics and that certain functions are globally Lipschitz, we can design a global reduced-order observer An illustrative example is included that demonstrate the design procedure of the proposed reduced-order observer.

In this paper, a variable structure controller(VSC) is used to control the position of the hydraulic servo system subjected to unknown disturbances. The system consists of two cylinders, which connected in series. One cylinder executes position control, the other executes force control to generate disturbances. In order to control each cylinder, interaction must be considered between two cylinders because two cylinders are connected in series. Therefore, the controller is designed regarding interaction between two cylinders as disturbances. Performance of the proposed controller was verified through experiments and compared to PID controller. The experiments showed that the proposed controller had a good performance and robustness.

In this paper, we develop control hardware such as an FPGA based general purposed intelligent controller with a DSP board to solve nonlinear system control problems. PID control algorithms are implemented in an FPGA and neural network control algorithms are implemented in a BSP board. An FPGA was programmed with VHDL to achieve high performance and flexibility. The additional hardware such as an encoder counter and a PWM generator can be implemented in a single FPGA device. As a result, the noise and power dissipation problems can be minimized and the cost effectiveness can be achieved. To show the performance of the developed controller, it was tested fur nonlinear systems such as a robot hand and an inverted pendulum.

In this paper, both dynamic constraints and kinematic constraints are considered for the analysis of manipulability of robotic systems comprised of multiple cooperating arms. Given bounds on the torques of each Joint actuator for every robot, the purpose of this study is to drive the bounds of task-space acceleration of object carried by the system. Bounds on each joint torque, described as a polytope, is transformed to the task-space acceleration through matrices related with robot dynamics, robot kinematics, object dynamics, grasp conditions, and contact conditions. A series of mathematical manipulations including the procedure calculating minimum infinite-norm solution of linear equation is applied to get the reachable acceleration bounds from given actuator dynamic constrains. Several examples including two robot systems as well as three robot system are shown with the assumptions of complete-constraint contact model(or' very soft contact') and insufficient or proper degree of freedom robot.

In this paper, an efficient real-time control architecture for autonomous navigation of powered wheelchair is developed. Since an advanced intelligent wheelchair requires real-time performance, the control software architecture of powered wheelchair is developed under Linux real-time extension Real-time Application Interface (RTAI). A hierarchical control structure for autonomous navigation is designed and implemented using real-time processe and interrupts handling of sensory perception based on slanted surface LRF, emergency handling capability, and motor control with 0.1 msec sampling time. The performance of our powered wheelchair system with the implemented control architecture for autonomous navigation is verified via experiments in a corridor.

This paper is concerned with a mixed control with aerodynamic fin and side thrust control applied to an agile missile using a dynamic inversion and a time-varying control technique. The nonlinear dynamic inversion method with the weighting function allocates the desired control inputs(aerodynamic fin and side thrust control) to achieve a reference command, and the time-varying control technique plays the role to guarantee the robustness for the uncertainties. The proposed schemes are validated by nonlinear simulations with aerodynamic data.

The Vehicle Dynamic Simulator(VDS) is a key equipment of the performance verification of attitude control subsystem and it simulates the real dynamic environment that spacecraft undergoes during mission operation. All the software models and hardware interfaces necessary for the closed-loop simulation of the spacecraft dynamics are implemented. Using VDS, KOMPAT-2 attitude control logic functions and performance was verified. In this paper, the hardware and software configurations of KOMPSAT-2 VDS was described briefly and the information flow and exchanges between software models and actual hardwares during close loop simulation was described in the systematic point of view.