Osman Parlaktuna

Adaptive control of free-floating space manipulators using dynamically equivalent manipulator model

Abstract In this paper, adaptive control of free-floating space manipulators is considered. The dynamics based on the momentum conservation law for the free-floating space manipulator has non-linear parameterization properties. Therefore, the adaptive control based on a linear parameterization model cannot be used in this dynamics. In this paper, the dynamics of the free-floating space manipulator system are derived using the Dynamically Equivalent Model (DEM) approach. The DEM is a fixed-base manipulator system and allows us to linearly parameterize the dynamic equations. Using this linearly parameterized dynamic equation, an adaptive control method is developed to control the system in joint space. Parameter identification and torque calculations are done using the DEM dynamics. Simulations show that the tracking errors of the manipulator joints to a given desired trajectory become zero when the calculated torques act on the joints of the space manipulator system.

Real-time tour construction for a mobile robot in a dynamic environment

Mobile robots are increasingly used in many areas. An optimum trajectory increases the effectiveness of a mobile robot. However, the environment may change dynamically which may require a real-time tour construction for the mobile robot. In this study, a heuristic-based TSP approach is applied to real-time dynamic tour construction problem for a mobile robot. Savings algorithm together with Dijsktras algorithm is used to determine a feasible tour for the mobile robot. The proposed method is applicable when the network is complete or sparse, directed or undirected. Experiments are conducted to show the effectiveness of the proposed algorithm.

Adaptive control of free-floating space robots in Cartesian coordinates

An adaptive control scheme is proposed for the end-effector trajectory tracking control of free-floating space robots. In order to cope with the nonlinear parameterization problem of the dynamic model of the free-floating space robot system, the system is modeled as an extended robot which is composed of a pseudo-arm representing the base motions and a real robot arm. An on-line estimation of the unknown parameters along with a computed-torque controller is used to track the desired trajectory. The proposed control scheme does not require measurement of the accelerations of the base and the real robot arm. A two-link planar space robot system is simulated to illustrate the validity and effectiveness of the proposed control scheme.

Jacobian control for space manipulator

Abstract Parlaktuna, O., Cook, G.E., Strauss, A.M. and Fernandez, K., Jacobian control for space manipulator, Robotics and Autonomous Systems, 11 (1993) 35–44. To control robot or teleoperated manipulators in space, the motion of the satellite (which is actually the base of the manipulator) which will move due to the force exerted by the moving manipulator, must be considered. Most of the algorithms developed to control a robot manipulator assume that the manipulator is connected to a fixed base. Since the satellite moves due to the motion of the robot manipulator, the control schemes developed for fixed-base manipulators cannot be used for space robots and telerobots. In this paper, using a modified resolved motion rate control and angular momentum conservation law, a generalized Jacobian matrix is derived to control the space manipulator. It is shown that a manipulator controlled in this manner follows a prescribed path independent of the motion of the satellite.

A novel sonar-based obstacle detection approach sensor-based coverage problem

In this paper, a vector-projection-based algorithm is developed to detect obstacles in narrow environments. This algorithm can be used for especially sensor-based coverage problems. The algorithm distinguishes the obstacles from the walls around the robot. Sonar vectors are projected on the edge which the robot moves to detect the obstacles. After detecting the obstacle, the size and location of the obstacle are calculated.

A new approach to improve the success ratio and localization duration of a particle filter based localization for mobile robots

In real world applications, it is important that mobile robots know their location to achieve goals correctly. The localization of the robot is difficult by using raw sensor data because of the noisy measurements from these sensors. To overcome this difficulty probabilistic localization algorithm approaches can be used. The Particle filter is one of the Bayesian-based methods. In this study, two new features incorporated into the particle filter approach. These features are: decreasing the size of sample space using compass data and a new sensor model. The proposed approach is applied in the localization problem of a mobile robot. Performance of the proposed algorithm is compared with the performance of traditional particle filter approach by changing several parameters of the system. These analyses emphasized that the proposed approach improved the localization performance of the system. The results are promising for the future studies on this subject.

Mobile robot navigation using fuzzy logic methods

In this study, a navigation algorithm for a mobile robot has been developed using fuzzy logic methods. Only the starting and destination coordinates are specified and robot travels form the starting point to the destination without having a priori knowledge of the environment. Therefore, robot can also travel in dynamic environments. Robot uses sonar range sensors and electronic compass in order to find its path and for obstacle avoidance. Fuzzy logic is used to model the environment and determining the behaviors.

TASK ALLOCATION IN MARKET-BASED APPLICATIONS BY THE NEAREST NEIGHBOR HEURISTIC

One of the main subjects that is studied in multi-robot applications is allocating tasks to robots and constructing objective-efficient tours for the robots using these allocated tasks. The main purpose of this paper is to allocate tasks via market-based task allocation architecture and to construct collision-free routes for multi-robot systems in a known indoor environment. For task allocation, a market-based architecture is constructed and applied to an example of a team of four heterogeneous mobile robots. In the study, tasks are allocated according to one of two constraints: minimizing the makespan of the robots and maximizing the robot task matching value of each robot in the group. These constraints are achieved by changing the value of a decision parameter. To show the effectiveness of the proposed method, comparisons are made within these constraints. To construct path, a combination of the Nearest Neighbor heuristic and Dijkstras shortest path algorithms is used. To construct non-conflicting paths, a method that detects and solves collisions is developed. In the study, for agent communication Open Agent Architecture is used. Additionally, simulations on the MobileSim platform are conducted to verify the feasibility of the proposed method.

Mobile robot localization using laser range sensor

In this study, localization of mobile robot is accomplished using laser range sensor and artificial landmark. It is assumed that mobile robot is positioned to sense the landmark and there is no other similar object to the landmark. First, using the properties of the laser range sensor, we calculate the range and angle at which landmark is sensed (i.e. how many laser beams will hite the landmark). Using these calculations possibly landmarks in a scan are transformed to the origin and error calculations are done at the origin. All of these calculations are done in a coordinate system on the robot, then a transformation is used to calculate the location of the robot relative to the world coordinate system.

Map making using ultrasonic range sensors

In this study, a mobile robot is used for map making using sonar range sensors on the robot. Map of the environment is drawn dynamically from the data obtained by the sensors. This map may be matched by a priori map of the environment which should be stored in the memory of the robot. The result of this matching can be used to overcome the self localization problem of a mobile robot. This study is conducted on a simulation platform which is developed for PIONEER mobile robots. Robot navigates in a corridor and makes the map of this corridor. Although there is some error in the corners, the algorithm is succesful in drawing the map of the corridor.