Search

The core idea of this study is developing a reliable method to manually guide robots in the physical cooperation scenarios, having human safety in priority. To this end, a safe human–robot cooperation algorithm in the presence of physical intentional interactions without employing force and vision sensors is developed. The physical interaction is recognized and controlled through available common sensors. Contact occurrence and its position are investigated by using online external torque vector obtained by residual based observer. Then, the force vector is estimated and employed in the suggested controller for manually guiding the robot. To completely handle the cooperation phase, four guiding scenarios based on actual conditions are recommended. Performance of the proposed controller-observer method during manipulation has been validated through multiple experiments on a KUKA LBR iiwa.

Manipulation and secure transportation of loads by robotic manipulators along predetermined paths is still an open challenge in the robotics field. In this article, the problem of pushing and driving an object on a surface employing a robot to reach a specific destination is considered under a-priori unknown friction conditions. For this purpose, the equations of motion are derived according to the limit surface conceptualization of friction force. Although friction parameters may be considered locally constant, nonetheless they gradually vary over large surfaces. The friction term is thus faced with a slowly time-varying indeterminacy and needs an online estimation scheme. By defining a mission consisting of pushing an object via a robot to find a path among obstacles, an optimum path is firstly planned then a non-linear model predictive controller is used to track the desired path. In order to alleviate the indeterminacy due to friction, the corresponding terms in the equations of motion are set as a disturbance which is estimated by a purposely designed observer and then eliminated in a feedforward manner. There is also no need to perform preliminary offline tests.

Dynamic analysis and trajectory tracking of a Tethered Space Robot (TSR) is investigated in this paper. A hybrid controller is used to perform the control task. It consists of two components, the first one deals with librational motion of the tether, while the second one takes care of the manipulator motion. A Nonlinear Model Predictive Control (NMPC) approach is used to control the tether libration; for this purpose, the libration is described by a single degree of freedom and the tether length rate is employed as the input to suppress the librational motion. A modified Computed Torque Method (CTM) is used to control the manipulator motion. The dynamic interaction between the manipulator motion and the librational motion is considered both in the system dynamics and control of the system. Using numerical simulations, performance of the proposed control system is evaluated for end-effector positioning as well as for trajectory tracking for two cases: a Low Earth Orbit (LEO) and the Geostationary Earth Orbit (GEO).

In present study, dynamic modeling and control of a tethered space robot system in trajectory tracking of its end effector is investigated. Considering variation of the tether length in the model, dynamics of the system is modeled using Lagrange’s method. Librational motion of the tether is controlled by adjusting the tether length similar to conventional manipulators,control of the robot is performed by its motors. It is clear that, in the trajectory tracking of the end effector, the tether length should be kept more or less constant, keeping them in a stable position. Limiting the tether length variation while using it as a tool for controlling the tether librational motion, is the main challenging part of the control system. To deal with this problem, a hybrid control system is proposed to control the system. A nonlinear model predictive control approach (NMPC) is utilized to control the tether librational motion and a modified computed torque method (CTM) is used to control the manipulator motion. Initially the NMPC controller is developed for a simple tethered satellite system. Then it is combined with the CTM controller.The proposed controller is employed to control motion of a space robot’s end effector on a predefined trajectory. Performance of the controller is then evaluated by numerical simulations.

Despite extensive studies on cyclic tasks in robotics, definitive solutions for the problem of trajectory generation for periodic motions have not been achieved so far. In this paper, we present an approach for online trajectory generation from a library of desired periodic trajectories. The proposed approach consists of a Central Pattern Generator (CPG) architecture ensuring entrainment of any periodic trajectory, smooth motion modulation and observing position and velocity limits of the robot. The proposed CPG is composed of a synchronized network of novel bounded output oscillatory systems. Every oscillatory system is a three-dimensional dynamical system encoding a one-dimensional periodic function as a stable limit cycle. We also use the state transformation method to bound the oscillator’s output and its first time derivative. Finally, we present a synchronization technique to construct a synchronized network of the proposed oscillators for generating multi dimensional periodic functions. Using Lyapunov based arguments, we prove that the proposed CPG ensures stability, convergence, and synchronization of the desired trajectory. The soundness of the proposed oscillator and the resulting CPG are validated both in simulations and experiments on the humanoid robot iCub.

SUMMARYConsidering undesired slippage between manipulated object and finger tips of a multi-robot system, adaptive control synthesis of the object grasping and manipulation is addressed in this paper. Although many studies can be found in the literature dealing with grasp analysis and grasp synthesis, most assume no slippage between the finger tips and the object. Slippage can occur for many reasons such as disturbances, uncertainties in parameters, and dynamics of the system. In this paper, system dynamics is analyzed using a new presentation of friction and slippage dynamics. Then an adaptive control law is proposed for trajectory tracking and slippage control of the object as well as compensation for parameter uncertainties of the system, such as mass properties and coefficients of friction. Stability of the proposed adaptive controller is studied analytically and the performance of the system is studied numerically.

In this paper, the problem of controlling a robot manipulator in task space, while guaranteeing a compliant behavior for the redundant degrees of freedom, is considered. This issue may arise in the case where the robot experiences an interaction on its body, especially in the presence of humans. The proposed approach guarantees correct task execution and compliance of the robot's body during intentional or accidental interaction in the null space of the main task, simultaneously. The asymptotic stability of the task-space error is ensured by using suitable observers to estimate and compensate the generalized forces acting on the task variables, without using joint torque measurements. Two different controller--observer algorithms are designed, and they are based on the task-space error and on the generalized momentum of the robot, respectively. The performance of the proposed algorithms is verified in experiments on a 7R lightweight robot arm.

Grasping an object by a cooperating system such as multi-fingered hands and multi-manipulator robotic system has received much attention. Research has focused on analysis of force-closure grasps an...

In this paper, the problem of controlling multiple different tasks in various points on the robot body is considered. The proposed approach guarantees the execution of multiple various tasks (force, position and orientation control) in the presence of intentional or accidental interaction with robot body. The control law distinguish between desired and accidental external forces. Magnitude and/or orientation of the forces in the contact points can be controlled while various tasks may be defined and controlled in other contact points in the robot body. Controller-observer algorithm is proposed based on the generalized momentum of the robot. Asymptotically stability of task space errors are proved while a proper estimation of the external torque on robot is available. Performance of the proposed algorithm is confirmed by simulations.

Assembling and fitting parts together can be considered as one of the most practical but also challenging process in robotics. Various applications are conceivable such as spatial ones where accessibility is reduced or in construction fields where huge forces have to be dealt with in a meticulous manner. In this paper, the cooperation of two robots during the complete assembling process of two structural parts from the approaching phase to the fitting stage is investigated. In the approaching phase for taking the parts closer, the two large construction parts may collide due to the inertia of motion, causing considerable impact forces even with the slightest relative velocity. This issue presents important control challenges as the effects of this local impact may be transferred throughout the system’s frame, affecting all other elements and inducing instability. Finally after connection of these two parts is established, the whole frame is transported to any desired location by cooperative operation of the two robots. Each step requires a particular controller to deal with different system’s dynamics that occur during the whole process.Copyright © 2014 by ASME

Ballbot is a mobile robot consists of a body mounting on a spherical wheel. The spherical wheel can make the robot move in any directions. This robot is an unstable underactuated system with nonholonomic velocity constraints. In this paper, first, a 3D dynamic model of the robot is derived while taking the nonholonomic constraints into considerations. Since Ballbot is an underactuated system, finding a normal form for the equations could be helpful in the control point of view. Therefore, the equations of motion are examined to find whether there is a simple normal form or not. To enforce the robot to track any given trajectory on the ground, an online fuzzy logic trajectory planning is suggested. A computed torque method and a sliding mode controller are used along the fuzzy trajectory planning to perform the tracking goal. To consider uncertainties and disturbances, some simulations are performed. The results show that the sliding mode controller demonstrate much better performance compared to the computed torque controller. When there is no uncertainty, the computed torque method is candidate showing less tracking error than the sliding controller.

SUMMARYThis paper presents a dynamic-level control algorithm to meet simultaneously multiple desired tasks based on allocated priorities for redundant robotic systems. It is shown that this algorithm can be treated as a general framework to achieve control over the whole body of the robot. The control law is an extension of the well-known acceleration-based control to the redundant robots, and considers also possible interactions with the environment occurring at any point of the robot body. The stability of this algorithm is shown and some of the previously developed results are formulated using this approach. To handle the interaction on robot body, null space impedance control is developed within the multi-priority framework. The effectiveness of the proposed approaches is evaluated by means of computer simulation.

This paper presents a dynamic level control algorithm to meet simultaneously multiple desired tasks based on allocated priorities for redundant robotic systems. It is shown that this algorithm can be treated as a general framework to achieve control over the whole body of the robot and some of the previously developed results are formalized using this approach. Null-space impedance control is proposed as one of the main results of using this method and is evaluated by means of computer simulation. © 2011 IEEE.

This paper describes design, Simulation and manufacturing procedures of HIRAD - a teleoperated Tracked Surveillance UGV for military, Rescue and other civilian missions in various hazardous environments. A Double Stabilizer Flipper mechanism mounted on front pulleys enables the Robot to have good performance in travelling over uneven terrains and climbing stairs. Using this Stabilizer flipper mechanism reduces energy consumption while climbing the stairs or crossing over obstacles. The locomotion system mechanical design is also described in detail. The CAD geometry 3D-model has been produced by CATIA software. To analyze the system mobility, a virtual model was developed with ADAMS Software. This simulation included different mobility maneuvers such as stair climbing, gap crossing and travelling over steep slopes. The simulations enabled us to define motor torque requirements. We performed many experiments with manufactured prototype under various terrain conditions Such as stair climbing, gap crossing and slope elevation. In experiments, HIRAD shows good overcoming ability for the tested terrain conditions.

In a structured dynamic environment, due to the known variation of the environment, robot trajectory planning can be performed robots motion starts. Within an unstructured dynamic environment, environment variations are permanent, so that the surroundings information must be acquired in an online action. Likewise the data acquisition, robot trajectory planning must be executed online. In this paper a method for online trajectory planning based on adaptive prediction planning and execution (APPE) is proposed for robotic manipulators considering velocity and torque constraints. A vision-based data acquisition system is used to acquire object positions and velocities. To describe the end-effector trajectories in joint and Cartesian space a set of time polynomial function are used. Initially a primary trajectory is planned and it will be updated in definite time periods. This action will be frequently repeated until catching is occurred. Proposed method has been tested on an experimental setup and the experimental results are presented.

In robot manipulators, inertia parameters of robot may be not known precisely and some dynamics such as friction torques that are usually difficult to be modelled and may be ignored. In this paper, we present a robust manipulator control approach that includes a feedback-feedforward compensation to compensate for the uncertain parameters and unmodeled dynamics and disturbances. The stability of the overall system is analyzed through Lyapunov direct method. For the proposed approach, global uniform asymptotic stability of the system is established. In addition, we present a continuous control law and guarantee the uniform ultimate boundedness of the tracking error. The simulation results are exhibited to support the theoretical issues.

Modifying the control algorithms to eliminate some sensors is a popular methodology to overcome the drawbacks associated with the using of these sensors. Complicating the structure of robot, impossibility to mounting on manipulator in high temperature and large noise, and high price are problems associated with the using of force/torque sensors. With this motivation, a scheme is presented in this paper to eliminate force/torque sensors. Desirable properties of the proposed scheme in the aspects of global uniform asymptotic stability, satisfactory estimation and effective tracking control are shown through strong detailed proofs and various simulation results.

Using kinematic resolution, the optimal path planning for two redundant cooperative manipulators carrying a solid object on a desired trajectory is studied. The optimization problem is first solved with no constraint. Consequently, the nonlinear inequality constraints, which model obstacles, are added to the problem. The formulation has been derived using Pontryagin Minimum Principle and results in a Two Point Boundary Value Problem (TPBVP). The problem is solved for a cooperative manipulator system consisting of two 3-DOF serial robots jointly carrying an object and the results are compared with those obtained from a search algorithm. Defining the obstacles in workspace as functions of joint space coordinates, the inequality constrained optimization problem is solved for the cooperative manipulators.

This paper presents a method for planning three-dimensional walking patterns for biped robots in order to obtain stable smooth dynamic motion and also maximum velocity during walking. To determine the rotational trajectory for each actuator, there are some particular key points gained from natural human walking whose value is defined at the beginning, end and some intermediate or specific points of a motion cycle. The constraint equation of the motion between the key points will be then formulated in such a way to be compatible with geometrical constraints. This is first done in sagittal and then developed to lateral plane of motion. In order to reduce frequent switching due to discrete equations which is inevitable using coulomb dry friction law and also to have better similarity with the natural contact, a new contact model for dynamic simulation of foot ground interaction has been developed which makes the cyclic discrete equations continuous and can be better solved with ODE solvers. Finally, the advantages of the trajectory described are illustrated by simulation results.