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On-orbit servicing, active debris removal or assembling large structures on orbit are only some of the tasks that could be accomplished by space robots. In all these cases, a contact between a space robot and the satellite being serviced, deorbited, or assembled will occur. This contact results in a contact force exerted on the space robot, and therefore momenta of the space robot system are no longer conserved. Most of the papers that are concerned with motion planning problems of a space robot manipulator either consider that no external forces or moments are acting on the space robot system or use additional controllers when the space robot is subjected to external forces and moments. Such a controller minimizes end-effector position and orientation errors caused by the changes in system momenta due to external forces and moments acting on this system. The novelty of this work is that it proposes a new method for planning the motion of dual-arm space robot manipulators when linear and angular momenta of the space robot system are not conserved due to external forces and moments acting on the space robot base or/and manipulators’ end-effectors. In the proposed method the changes in system momenta are considered, but no additional controllers are needed. In this paper, we derive the motion planning equations for dual-arm space robot manipulators, where external forces and moments are acting on both satellite and manipulator end-effectors. The proposed method has been verified by numerical simulations, and the results are presented and discussed.

This paper examines accurate image depth determination to achieve accurate navigation. Accurate navigation is critical for Unmanned Aerial Vehicle or UAV aerial refueling and, also, space debris clearance operations. At this point it is not the intention to generate a definitive depth performance study, rather the intention is to gain an understanding of the kind of depth performance which might be possible for a small UAV or space-based robot flying close in and far away, at depths of 2 and 20 m, for example. The theory behind image depth calculation is explained and then synthetic pixel data are manufactured to determine a 95% confidence interval on image depth under various errors conditions. It is shown that without image rectification and no knowledge of camera rotation, accurate depth can only be calculated for stereo cameras pointing without any axial rotations. With image rectification and under the stated conditions, image depth can be calculated with 8.2% or less absolute relative error. Future research is discussed.

This paper present and discusses algorithms suitable for visual navigation for mobile and flying robots. Three different algorithms were used to explore the direct method for the vision system. Those methods are Homography, Iterative Closest Point (ICP), and Horn’s Absolute Orientation. Those algorithms were tested on the camera with moving baseline. The relations between optimal baseline and depth distance were discussed. The camera’s calibration process has been presented and discussed. Several experiments with the different image noise level were performed. The noise levels influence on distance and pose estimation accuracy were discussed. Measurements and estimation errors for both mobile and flying robots were shown and compared with different methods.

The paper compares control strategies for four flexible space robot manipulators including the classical Slotine and Li algorithm, a simple proportional derivative controller, a singular perturbation-based controller and a nonlinear backstepping controller. All strategies are tested and compared in simulations involving endpoint target positioning while tracking a square trajectory by a two-link flexible joint space robot. Simulation results indicate that controlling both nonlinearities and joint flexibility effects improve the closed-loop behavior of the space robot where the control of nonlinearities is of greater importance. The best performance is achieved by the nonlinear backstepping control strategy. We also propose Hammerstein nonlinear joint model and introduce its nonparametric nearest neighbor kernel identification algorithm and study its convergence.

Robots mounted on an unmanned chaser satellite could be used for performing rendezvous and grasping manoeuvres in order to repair satellites or remove space debris from orbit. Use of manipulators for such purposes is challenging, since the performed task need to be done autonomously, accurately and with high level of robustness. During manoeuvres high disturbances might appear e.g. due to contact between the manipulator arm end-effector and the target spacecraft. In this paper an approach for validation of the robotic subsystem during chaser rendezvous and grasping manoeuvre has been shown. Two type of testbed systems were used: planar air-bearing microgravity simulators and a test-bed system with industrial robots. The proposed approach took advantage of possible replacement of particular subsystem in reference model or reference hardware in specified test-bed system. The list of tests performed are included in the paper.

A smart fire detection system is a necessary part of a smart manufacturing facility. Autonomous robots may be deployed to seek out a potential source of fire in the industrial environment, approach, investigate and declare the presence or absence of fire based on several sensor fusion techniques. A novel approach of the above mentioned topic is described in this paper. A new technique, introduced as “Modified Voting Logic” is explained. The robot uses sensor readings comparison to approach the source and a smart obstacle avoidance system to avoid obstacles together with Modified Voting Logic to declare a fire threat.

Growing research interest in space robotic systems capable of accurately performing autonomous manipulation tasks within an acceptable execution time has led to an increased demand for lightweight materials and mechanisms. As a result, joint flexibility effects become important and represent the main limitation to achieving satisfactory trajectory-tracking performance. This paper addresses the nonlinear adaptive output feedback control problem for flexible-joint space manipulators. Composite control schemes in which decentralized simple adaptive control-based adaptation mechanisms to control the quasi-steady-state robot model are added to a linear correction term to stabilize the boundary-layer model are proposed. An almost strictly passivity-based approach is adopted to guarantee closed-loop stability of the quasi-steady-state model. Simulation results are included to highlight the performance and robustness of the proposed adaptive composite control methodologies to parametric and dynamics modeling unce...

Mobile robot formations differ in accordance with the mission, environment, and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations needs to be built in the controllers of each autonomous robot. In this paper, self-organizing formations control for material transfer is investigated, as an alternative to automatic guided vehicles. Leader–follower approach is applied for controllers design to drive the robots toward the goal. The results confirm the ability of velocity potential approach for motion control of both self-organizing formations.

Mobile robot formations differ in accordance to the mission, environment and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations needs to be built in the controllers of each autonomous robot. In this paper is investigated self-organizing formations control for material transfer, as an alternative to Automatic Guided Vehicles (AGVs). Leader-follower approach is applied for controllers design to drive the robots toward the goal. The results confirm the ability of velocity potential approach for motion control of both self-organizing formations.

Operational problems with robots in space relate to several factors. One of the most important factors is the elastic vibrations in the joints. In this paper, control strategies for endpoint tracki...

Mobile robot formations differ in accordance to the mission, environment and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations has to be built in the controllers of each autonomous robot. In this paper two types of basic formations are investigated: self-organizing and geometric. Leader follower approach is applied for controllers design to drive the robots toward the goal. Simulations show that that self-organizing formations tend toward platoon formation. Geometric formations approach is also simulated for the case of V-formations passing through a passage. The results confirm the ability of velocity potential approach for motion control of both self-organizing and geometric formations

This paper presents a comparative study of four control strategies for a flexible joint space manipulator. The considered control strategies consist in the classical Slotine and Li algorithm, a simple proportional derivative controller, a singular perturbation-based controller and a nonlinear backstepping controller. All control methodologies are assessed in numerical simulations for endpoint positioning while tracking a 12.6 × 12.6 m square trajectory by a two-link flexible joint space robot, thus providing a common framework to compare the respective performance of the considered control schemes. Simulation results indicate that controlling both nonlinearities and joint flexibility effects improve the closed-loop behavior of the space robot where the control of nonlinearities is of greater importance in the sense that it provides the most significant improvements. While each control scheme tracks the trajectory with a different degree of accuracy, the best performance for this particular application is obtained with the nonlinear backstepping control strategy.

Inverse flexible dynamics control (IFDC) and fuzzy logic system adaptive control (FLSAC) strategies are used to track the end effector of a flexible space robot with sensors collocated at the joints, noncollocated at the end effector and 0.5m from the elbow joint on link 2. Collocated joint sensors satisfy hyperstability conditions but fail to capture nonminimum phase (NMP) response that generates time-delays causing asynchronous control action. Noncollocated sensors capture NMP response but require time delay compensation to achieve synchronous control action. Results for IFDC are insignificant compared to those achieved with FLSAC.

This paper demonstrates a haptic device for interaction with a virtual environment. The force control is added by visual feedback that makes the system more responsive and accurate. There are two popular control methods widely used in haptic controller design. First, is impedance control when user motion input is measured, and then, the reaction force is fed back to the operator. The alternative method is admittance control, when forces exerted by user are measured and motion is fed back to the user. Both, impedance and admittance control are also basic ways for interacting with a virtual environment. In this paper, several experiments were performed to evaluate the suitability of force-impedance control for haptic interface development. The difference between conventional application of impedance control in robot motion control and its application in haptic interface development is investigated. Open loop impedance control methodology is implemented for static case and a general-purpose robot under open loop impedance control was developed as a haptic device, while a closed loop model based impedance control was used for haptic controller design in both static and dynamic case. The factors that could affect to the performance of a haptic interface are also investigated experimentally using parametric studies. Experimental results for 1 DOF rotational motion and 2 DOF planar translational motion systems are presented. The results show that the impedance control aided by visual feedback broaden the applicability of the haptic device and makes the system more responsive and accurate.

This paper presents the model, simulation and experimental results of model predictive control (MPC) for motion control of an autonomous vehicle. The simulation and experiments were designed for mining application. In mining industry robotic vehicles have to navigate in tunnels and often have to overcome inclined and rough surfaces. In this case, the MPC was applied using a three-dimensional dynamic model of the robot vehicle. The purpose is to achieve autonomous vehicle motion with the avoidance of wheel-ground slippage or loss of contact while, at the same time, conserving the geometric path planning results by modifying the input commands. Tests were carried out for a vehicle moving on an inclined plane. Results from testing MPC plus feedback linearization controllers are presented and compared with results for controllers using only feedback linearization. Simulation results are presented for a three-wheeled vehicle moving in conditions that permit to illustrate the performance of the proposed controller. The results obtained show that the MPC is an efficient method that contributes to accurate control and navigation of an autonomous vehicle. The results were used to evaluate the performance and operational capabilities of an autonomous unmanned mining vehicle.

Operational problems with robot manipulators in space relate to several factors, one most importantly being structural flexibility and subsequently significant difficulties with the control systems, especially, position control. A control strategy is devised for positioning the endpoint of a two-link robot manipulator modeled with assumed modes flexible dynamics repetitively tracking a square trajectory. The dominant assumed modes of vibration are determined for Euler-Bernoulli cantilever beam boundary conditions then, coupled with the nonlinear dynamics for rigid links to fonn an Euler-Lagrange inverse flexible dynamics robot model. A Jacobian transpose control law actuates the robot links. While repetitive tracking alone achieves no improvement in control precision, adapting the control law by a fuzzy logic system achieves consistent tracking precision.

Autonomous robots are required to avoid the obstacles during navigation. For this purpose unknown and unexpected obstacles have to be detected during motion. The proposed approach uses particle filters to process sensors data and estimate relative position of the robot with regard to the obstacles and to the goal. These relative position estimations are inputs to the velocity potential field approach for obtaining time varying velocity commands for the robot to avoid all obstacles and reach the goal.

This paper presents the sensor fusion for dead-reckoning mobile robot navigation. Odometry and sonar measurement signals are fused together using Extended Kalman Filter (EKF) and Adaptive Fuzzy Logic System (AFLS). Two methods of adaptation scheme are used, the first one uses Q and R , the second one only uses Q . The first method gives faster result than the second one. The fused signal is more accurate than any of the original signals considered separately. The enhanced, more accurate signal is used to guide and navigate the robot.

Simultaneous localization and mapping is a situation in which a mobile robot travels through an environment and concurrently makes a momentary map of the environment and uses that map to localize. The simultaneous localization and mapping is currently one of the most challenging problems in the field of autonomous mobile robots and providing a solution to SLAM may open doors to the world of truly autonomous robots. This paper provides a novel approach to Simultaneous Localization and Mapping problem based on estimation approach. The new approach is called Unscented HybridSLAM filter which addresses the linearization process of an autonomous mobile robot utilizing the second order Sterling polynomial interpolation specifically used for Unscented HybridSLAM algorithm. Using computer simulations, Unscented HybridSLAM and the associated theoretical interpolation is examined for a double-loop scenario and the efficacy of the Unscented HybridSLAM is validated.

Formations required to move to given destinations can be controlled to arrive to a predefined geometric shape or to self-organize. For a large number of autonomous mobile robots, geometric formations pose too many constraints to achieving inter-robot positions. Self-organizing formations are more suitable for a large number of robots and generate formation shapes while avoiding robots collisions. In this paper are investigated approaches for self-organizing formations of large number of robots. The approach, inspired by hydrodynamic flow, results in an artificial velocity field approach that avoids local minima due to a combination of normal and tangential velocity commands associated to obstacles. These commands, for the formation of a large number of robots that are all subject to a velocity vector command to move to the goal, avoid inter robots collisions. In this paper is investigated the efficiency of this control approach in generating a formation shape and maintaining it during motion while moving toward a goal. Experimental and simulation results confirm the applicability of this control approach.

Autonomous robots can be equipped to detect potential threats of fire and find out the source while avoiding the obstacles during navigation. The proposed system uses Voting Logic Fusion to approach and declare a potential fire source autonomously. The robot follows the increasing gradient of light and heat to identify the threat and approach source.

This paper presents a control system for guidance and navigation of a mobile planetary rover. The control system is composed of three subsystems. The path tracking is accomplished using the LQR algorithm. The position and orientation errors are feedback using optimal gains. The disturbances are feedforward to improve the transient responses of the rover. Position and orientation errors are measured using odometry and inertial navigation system (INS). The collision avoidance is performed using the artificial potential field method. The data for that control loop is acquired using a scanning rangefinder. Dead reckoning is improved by using filtering and fusing signals from INS and odometry. Extensive simulation results and partial experimental results have been shown.

Growing research interest in space robotic systems capable of accurately performing autonomous manipulation tasks within an acceptable execution time has led to an increased demand for lightweight materials and mechanisms. As a result, joint flexibility effects become important, and represent the main limitation to achieving satisfactory trajectory tracking performance. This paper addresses the nonlinear adaptive output feedback control problem for flexible-joint space manipulators. Composite control schemes in which decentralized simple adaptive control-based adaptation mechanisms to control the quasisteady state robot subsystem are added to a linear correction term to stabilize the boundary layer subsystem, are proposed. An almost strictly passivity-based approach is adopted to guarantee closed-loop stability of the quasi-steady state subsystem. Simulation results are included to highlight the performance and robustness to parametric uncertainties and modeling errors of the proposed composite control methodologies.

Mobile robot formations differ in accordance to the mission, environment and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations has to be built into controllers of each robot. In this paper the use of velocity potential approach for controlling formations of robots in crowded environments is investigated. Several physical experiments and extensive simulations tests were performed and discussed.

Mobile robot formations differ in accordance to the mission, environment and robot abilities. In the case of decentralized control, the ability to achieve the shapes of these formations has to be built in the controllers of each robot. In this paper two types of basic formations are investigated, platoon and V-shape. Leader follower approach is applied for controllers design to drive each robot toward achieving the desired geometric shape of the formation.

Control of the flexible arm space based robots in general is a difficult problem. Low damping and significant flexibility cause vibration and non-linear phenomenon. This paper presents a control system for a flexible arm using piezofilm sensors and piezoceramic actuators. LQR method, based on a full state feedback, has been used to control the flexible arm. The control system has been studied both analytically and experimentally. Results are compared and discussed. The paper shows that piezoelements can be efficient components of control systems especially in case where several dynamic modes have to be compensated.

An adaptive fuzzy logic control scheme is developed for tracking a square trajectory by the endpoint of a two-link rigid joint space robot. The control strategy is based on a direct adaptive control scheme in which the controller gains are adapted in real-time according to fuzzy logic systems such that the tracking errors between a reference model and the actual robot system outputs are brought to zero.

Lightweight space robotic systems are known to exhibit elastic effects in their gearboxes, which contribute greatly to the motion of their end-effector. When accurate end-effector positioning is required, such flexible joint vibrations must be taken into account in both the modeling and control of space manipulators. This paper presents an analysis and a comparative numerical simulation study of previous studies on advanced control schemes for flexible joint robots. More specifically, a linear PD control, a rigid-based indirect adaptive control, an indirect adaptive composite control, a nonlinear backstepping control, a transpose Jacobian composite control, and a direct adaptive composite control methodologies are considered. The performance of the controllers is illustrated in a 12.6 × 12.6 m square trajectory tracking scenario by a two-link flexible joint space manipulator.

An adaptive control scheme is proposed for tracking a 12.6 − 12.6 m square trajectory by the endpoint of a two-link rigid joint space robot. The adaptive controller is based on the classical Transpose Jacobian control law where the controller gains are adapted using a modified version of the Simple Adaptive Control (SAC) adaptation law. The formal Lyapunov proof of stability for the adaptive control system is derived. Simulation results show that the proposed adaptive control methodology is a promising concept when applied to space robots and yields improved tracking results compared to a nonadaptive control strategy.

This paper presents the current state of the technology in space robotics. Some historical developments and the experience gained during those projects have been discussed. The challenge of space exploration and related danger requires even larger use of robotics devices. Many tasks and jobs are being automated. The exploration of the Moon and Mars requires the autonomous, mobile robots to gather various information, measurements and data. An introduction of Space Shuttle and related activities required an efficient robotic manipulator for in orbit operations. The Space Station Mir (in orbit) and especially Space Station Freedom (planned for nearest future) require advanced robots and manipulators. The Space Station Remote Manipulator System (SSRMS) and Special Purpose Dextrous Manipulator (SPDM) have been shown and briefly reviewed. Those and other robots for future missions are discussed in this paper.

Autonomous navigation in an outdoor environment can be effectively performed by small robots but remains a challenging task as soon as real scale ground vehicles are concerned. An intelligent mobile robot which uses a real armor ground vehicle as a platform is currently being developed for security applications (Fig. 30.1(a)). The robot tasks needed to be addressed are patrolling, surveillance, and tracking suspicious objects in a limited area. Executing those tasks a security robot often faces the situation when many objects in the environment have similar geometrical characteristics. This situation is typical for navigating within the outdoor warehouse [1] as illustrated in Fig. 30.1(b). The cargo containers (the squares with pattern) of the same size are piled inside the fenced area. A robot is used to carry out the patrol along a given trajectory (dotted line) around the area. Being equipped with the basic positioning system using GPS receiver and odometry sensor, a robot is able to follow the given path if measurement no errors are negligible. In practice, due to various errors (misalignments, drifts, slippage) basic GPS/odometry-based system fails to provide reliable pose estimates required in physically restricted environments. Measurements of relative distances are necessary and they are provided in our case by an additionally installed laser range sensor (LRS) known for its accuracy and reliability.

This paper presents a navigation of an autonomous robot using simultaneous localization and mapping (SLAM) in outdoor environments. SLAM is a method in which localization and mapping are done simultaneously in an unknown environment without an access to a priori map. This paper introduces a probabilistic approach to a SLAM problem under Gaussian and non-Gaussian conditions and offers alternative solutions. First, an extended Kalman filter algorithm for the SLAM problem under Gaussian condition will be shown. Also, an alternative way of dealing with SLAM problem with assumption of non-Gaussian and called FastSLAM will be analyzed. FastSLAM is an algorithm that using Rao-Blackwellised method for particle filtering, estimates the path of robot while the landmarks positions which are mutually independent and with no correlation, can be estimated by EKF. This is done using a factorization that fits very well into SLAM problem based on a Bayesian network. In this paper, a real outdoor autonomous robot is presented and several experiments have been performed based on both methods. The experimental results are discussed and compared.

This paper presents a model of force interaction between the two-arm robot and a load handled by the robot. The model is applied to dual force-position control of a two-arm robot. Since position control and force control are closely interrelated, the design and implementation of such a hybrid (force + position) control system is a comlex task. When two-arm manipulators are used to handle objects, a force control system has to be employed in order to protect the body from slippage out of grasp. The force control works simultaneously with a position control. A multi-level adaptive control system based on a reference model is presented in this paper. A simulation study has been performed to evaluate the performance of the proposed control scheme.

Operational problems with space robots relate to several factors, one most importantly being structural flexibility and subsequently significant difficulties with position control. Elastic link vibrations with inherent nonminimum phase response coupled with large rotations create a complex nonlinear dynamic system for control. The ability of the flexible robot to follow a prescribe trajectory is an important issue. In case of more complex operation, good tracking control could potentially save much time and money. This paper compares the performance of control strategies with noise filtering, then combined with nonminimum phase and corrective control action modeled by time delays for a stationary spacecraft mounted flexible robot tracking a 12.6 m × l2.6 m square trajectory. Finally a fuzzy logic system (FLS) vibration suppression strategy demonstrates its effectiveness in providing intelligent and autonomous precision control. The inclusion of this fuzzy logic approach to vibration suppression is motivated by the prospect of substituting for the control of space robotic systems typically teleoperated by astronauts. Tracking results are obtained initially without vibration suppression or noise filtering, then with EKF and FLAEKF state estimators to determine tracking accuracy for robot process and measurement noise. Time delays are included in the feedback and control action loops to simulate nonminimum phase response and corrective control. Finally, a FLS is used to adapt the control law and suppress residual vibrations. Good tracking results were previously achieved using an input shaping method to reduce residual vibrations coupled with an inverse kinematics control strategy and recursive order-n algorithm to model a two-link flexible robot tracking a square trajectory [1].

The end effector of a free-flying flexible space robot is tracked along a planar trajectory using inverse flexible dynamics control (IFDC) and fuzzy logic system adaptive control (FLSAC) strategies for comparison. The robot is required to track its end effector between two points in two-dimensional space while maintaining the orbiting rigid spacecraft at a fixed position in space. Simulation results show the IFDC strategy produces a trajectory that fails to reach its commanded final position by a large margin in both coordinates. The FLSAC strategy produces a more accurate trajectory closer to the commanded final position in both coordinates but at a greater computational time burden. Sporadic high magnitude driving torque “spikes” are experienced similar to the “bursting phenomenon” encountered with adaptive control systems. Spacecraft reactive translation and attitude disturbance is minimal in each case but slightly greater for IFDC. Notation

Navigation of autonomous vehicles and robots can be divided into two categories: indoor navigation and outdoor navigation. In general the outdoor navigation is more difficult and complex task because often the environment does not have characteristic points that can be identified and with respect to which robots could relate their position. If environment is unstructured (e.g. off-road environment), problems related to autonomous navigation are very difficult. Problems related to navigation in the unstructured environment could be divided into mapping, localization, collision avoidance and trajectory tracking.

Tracking a flexible robot is simulated using nonadaptive and fuzzy logic system (FLS) adaptive control strategies with noncollocated joint rotation sensors then with a position sensor located 0.5m, 2.25m and 4.0m from the end effector. Collocated joint rotation sensors satisfy hyperstability conditions but fail to capture nonminimum phase (NMP) response that causes control action delay. A position sensor noncollocated at the end effector captures NMP response. Results are poor for nonadaptive control with a collocated rotation sensor and a noncollocated end effector position sensor but very good results are achieved for FLS adaptive control. For noncollocated sensors at 0.5m, 2.25m and 4.0m from the end effector, tracking control results for both strategies are similar but drastically deviate from the commanded trajectory as the sensor gets closer to the elbow joint. FLS adaptive control is most effective for a sensor located either at the elbow joint or end effector.

†Operational problems with robot manipulators in space relate to several factors, one most importantly being structural flexibility and subsequently significant difficulties with the control systems, especially, for position control. This paper presents a comparison of fuzzy logic system (FLS) controllers to determine an optimal design for tracking the endpoint of a two-link flexible robot. The dominant assumed mode of vibration for an EulerBernoulli cantilever beam is coupled with the nonlinear dynamics for rigid links to form an Euler-Lagrange inverse flexible dynamics robot model. A Jacobian transpose control law is adapted by a FLS with link deformation inputs and a single variable output. Simulation results for three, five, seven and nine triangular and Gaussian membership functions are compared to identify an optimal design for best tracking control and least computation time. Results show the optimal choice of FLS is three triangular membership functions at 14 min 51 sec tracking time.

rigid Euler-Lagrange dynamics model but are extended here to a flexible dynamics model based on the first assumed mode calculated using Euler-Bernoulli pinnedpinned beam theory. A square trajectory presents an ideal case for studying intense vibration effects and their control at the four orthogonal direction switches. 7 Operational problems with robots in space relate to several factors. One most important is the structural flexibility problem of a robot manipulator and subsequently significant difficulties with its control systems, especially, position control. Typically, small elastic vibrations of the links coupled with their large rigid link rotations and non-linear dynamics primarily cause these difficulties. This paper presents a control scheme for positioning the endpoint of a two-link robot manipulator modeled with assumed modes flexible dynamics while tracking a square trajectory. The dominant assumed mode vibration is derived for an Euler-Bernoulli pinned-pinned beam to model link flexibility then, coupled with nonlinear dynamics for large rotations of rigid links to formulate an EulerLagrange inverse dynamics robot model. A control law derived using the Jacobian transpose provides joint actuation for both rigid and flexible dynamics. Comparison of output trajectories shows some differences in control performance between the rigid and flexible dynamics models with the transient response characteristics demonstrating a reduction in maximum overshoot for the flexible dynamics over the rigid dynamics models but a lengthier settling time with a consistent albeit slight oscillation about the entire desired steady-state ttrajectory .

Aerial robots can be considered as the natural evolution of the Unmanned Aerial Vehicles (UAVs) from the point of view of the intelligence. Traditional industrial robots evolved from the repetition of sequences of previously defined way points, with minimal perception and decision capabilities, toward robots interacting with the environment, mapping unknown environments and localising the robot in these maps. Thus, Simultaneous Localisation and Mapping (SLAM), has played an important role in the exploration of unknown environments. In the same way, Unmanned Aerial Vehicles will also evolve from the current commercial UAVs that mainly move by following a list of way points, to aerial robots capable of perceiving the environment adapting their behaviour to dynamic events. In addition, current UAV navigation strongly depends on satellite positioning systems, and then is sensitive to GPS transient failures, which are common in many outdoor environments. Furthermore, the navigation in GPS denied environments requires positioning devices that could be very costly and/or difficult to be implemented. Therefore, positioning with respect to the perceived environment is a need to increase the reliability or even to make possible UAV navigation. Moreover, environment mapping is also a very desirable feature for many UAV applications. Consequently, simultaneous

This paper presents the current state of the technology in space robotics. Some historical developments and the experience gained during those projects have been discussed. The challenge of space exploration and related danger requires even larger use of robotics devices. Many tasks and jobs are being automated. The exploration of the Moon and Mars requires the autonomous, mobile robots to gather various information, measurements and data. An introduction of Space Shuttle and related activities required an efficient robotic manipulator for in orbit operations. The Space Station Mir (in orbit) and especially Space Station Freedom (planned for nearest future) require advanced robots and manipulators. The Space Station Remote Manipulator System (SSRMS) and Special Purpose Dextrous Manipulator (SPDM) have been shown and briefly reviewed. Those and other robots for future missions are discussed in this paper.