An algorithm for the tele-operation of mobile-manipulator systems with a focus on ease of use for the operator is presented. The algorithm allows for unified, intuitive, and coordinated control of mobile manipulators. It consists of three states. In the first state, a single 6-degrees-of-freedom (DOF) joystick is used to control the manipulator's position and orientation. The second state occurs when the manipulator approaches a singular configuration, resulting in the mobile base moving in a manner so as to keep the end-effector travelling in its last direction of motion. This is done through the use of a constrained optimization routine. The third state is entered when the operator returns the joystick to the home position. Both the mobile base and manipulator move with respect to one another keeping the end-effector stationary and placing the manipulator into an ideal configuration. The algorithm has been implemented on an 8-DOF mobile manipulator and the test results show that it is effective at moving the system in an intuitive manner.

We present a review of recent activities in swarm robotic research, and analyse existing literature in the field to determine how to get closer to a practical swarm robotic system for real world applications. We begin with a discussion of the importance of swarm robotics by illustrating the wide applicability of robot swarms in various tasks. Then a brief overview of various robotic devices that can be incorporated into swarm robotic systems is presented. We identify and describe the challenges that should be resolved when designing swarm robotic systems for real world applications. Finally, we provide a summary of a series of issues that should be addressed to overcome these challenges, and propose directions for future swarm robotic research based on our extensive analysis of the reviewed literature.

Central Pattern Generators (CPGs) can generate robust, smooth and coordinated oscillatory signals for locomotion control of robots with multiple degrees of freedom, but the tuning of CPG parameters for a desired locomotor pattern constitutes a tremendously difficult task. This paper addresses this problem for the generation of fish-like swimming gaits with an adaptive CPG network on a multi-joint robotic fish. Our approach converts the related CPG parameters into dynamical systems that evolve as part of the CPG network dynamics. To reproduce the bodily motion of swimming fish, we use the joint angles calculated with the trajectory approximation method as teaching signals for the CPG network, which are modeled as a chain of coupled Hopf oscillators. A novel coupling scheme is proposed to eliminate the influence of afferent signals on the amplitude of the oscillator. The learning rules of intrinsic frequency, coupling weight and amplitude are formulated with phase space representation of the oscillators. The frequency, amplitudes and phase relations of the teaching signals can be encoded by the CPG network with adaptation mechanisms. Since the Hopf oscillator exhibits limit cycle behavior, the learned locomotor pattern is stable against perturbations. Moreover, due to nonlinear characteristics of the CPG model, modification of the target travelling body wave can be carried out in a smooth way. Numerical experiments are conducted to validate the effectiveness of the proposed learning rules.

This paper proposes a precise outdoor localization algorithm with the integration of Global Positioning System (GPS) and Inertial Navigation System (INS). To achieve precise outdoor localization, two schemes are recently proposed, which consist of de-noising the INS signals and fusing the GPS and INS data. To reduce the noise from the internal INS sensors, the discrete wavelet transform and variable threshold method are utilized, and to fuse the GPS and INS data while filtering out the noise caused by the acceleration, deceleration, and unexpected slips, the Unscented Particle Filter (UPF) is adopted. Conventional de-noising methods mainly employ a combination of low-pass and high-pass filters, which results in signal distortion. This newly proposed system also utilizes the vibration information of the actuator according to the fluctuations of the velocity to minimize the signal distortion. The UPF resolves the nonlinearities of the actuator and non-normal distributions of the noise more effectively than the conventional particle filter (PF) or Extended Kalman Filter–PF. The superiority of the proposed algorithm was verified through experiments, and the results are reported.

This study addresses the kinematics of a six-degrees-of-freedom parallel manipulator whose moving platform is a regular triangular prism. The moving and fixed platforms are connected to each other by means of two identical parallel manipulators. Simple forward kinematics and reduced singular regions are the main benefits offered by the proposed parallel manipulator. The Input–Output equations of velocity and acceleration are systematically obtained by resorting to reciprocal-screw theory. A case study, which is verified with the aid of commercially available software, is included with the purpose to exemplify the application of the method of kinematic analysis.

The paper examines the problem of dynamic ship positioning with the use of Kalman Filter- and Particle Filter-based sensor fusion algorithms. The proposed approach enables to estimate accurately the ship's state vector by fusing the vessel's position and heading measurements coming from on-board sensors together with distance measurements coming from sensors located at the coast (e.g. radar). The estimated state vector is used in turn, in a control loop, to regulate the horizontal position and heading of the vessel. The performance of dynamic positioning of the ship based on Kalman and Particle Filtering is evaluated through simulation experiments.

There is an increasing popularity of mobile robot applications over the Internet. Robots need some kind of wireless communication to receive commands and transmit information to users. This paper describes the problems encountered to keep the mobile robots connected and the solutions adopted. The first problem was related to delays and the very low throughput that occur when the robot roams to a new access point. Most commercial systems currently installed implement proprietary solutions with different behaviors. Here, a simple and device-independent solution for mobile robot applications is proposed. The second problem is the lack of wireless coverage in some areas of buildings. The solutions adopted for these problems are based on coverage maps.

In this paper, Clifford Algebra is used to model and facilitate solving the inverse kinematic problem for robots with only two consecutive parallel axes. It is shown that when a solution exists, it is usually the case that one of the angles of rotation can be arbitrarily chosen from a union of intervals. The remaining angles are then uniquely determined. Of course, there are cases when no solution exists, such as when the object is out of reach. But typically, when solutions exist, there are infinitely many sets of solutions.

In this paper, a model-based exponential stabilization of a quadruped robot is studied in bounding motion. The dynamics of the five-link planar underactuated mechanical model of the quadruped robot with four actuated joints system is derived. It is shown that the dynamical equation of the proposed simplified model belongs to a class of second-order nonholonomic mechanical systems which cannot be stabilized by any smooth time-invariant state feedback. Utilizing a coordinate transformation based on the so-called normalized momentum, a robust backstepping control method is presented for the quadruped robot. Both theoretical analysis and numerical simulations show that the robust backstepping controller can stabilize the underactuated quadruped robot so that it could balance on its rear legs and track a desired trajectory. Despite the model parameter uncertainties, the robustness of the controller is maintained. The simulation results show the effectiveness of the proposed method.

Human reaction to external stimuli can be investigated in a comprehensive way by using a versatile virtual-reality setup involving multiple display technologies. It is apparent that versatility remains a main challenge when human reactions are examined through the use of haptic interfaces as the interfaces must be able to cope with the entire range of diverse movements and forces/torques a human subject produces. To address the versatility challenge, we have developed a large-scale reconfigurable tendon-based haptic interface which can be adapted to a large variety of task dynamics and is integrated into a Cave Automatic Virtual Environment (CAVE). To prove the versatility of the haptic interface, two tasks, incorporating once the force and once the velocity extrema of a human subject's extremities, were implemented: a simulator with 3-DOF highly dynamic force feedback and a 3-DOF setup optimized to perform dynamic movements. In addition, a 6-DOF platform capable of lifting a human subject off the ground was realized. For these three applications, a position controller was implemented, adapted to each task, and tested. In the controller tests with highly different, task-specific trajectories, the three robot configurations fulfilled the demands on the application-specific accuracy which illustrates and confirms the versatility of the developed haptic interface.

This paper looks at the inverse kinematics problem of an a priori unknown 6R-Robot from the representation point of view. It describes a new representation of the Euclidean motion group. With this representation, the inverse kinematics problem can be treated entirely numerical. No symbolical methods are required.

Addition of extra sensors, especially video cameras and force sensors, under control of appropriate software makes robotic manipulators working in factories suitable for a range of new applications. This paper presents a method of manipulator indirect force control development, in which the force set values are specified in the operational space and the manipulator is equipped with a force sensor in its wrist. Standard control development methods need the estimation of parameters of the detailed model of a manipulator and position servos, which is a complicated and time-consuming task. Hence, in this work a time-efficient hybrid procedure of controller development is proposed consisting of both analytical and experimental stages: proposal of an approximate continuous model of a manipulator, experimental determination and verification of its parameter values using the resonance phenomenon, continuous regulator development, and digitization of the regulator.

This paper proposes an image sequence-based navigation method under the teaching-replay framework for robots in piecewise linear routes. Waypoints used by the robot contain either the positions with large heading changes or selected midway positions between junctions. The robot applies local visual homing to move between consecutive waypoints. The arrival at a waypoint is determined by minimizing the average vertical displacements of feature correspondences. The performance of the proposed approach is supported by extensive experiments in hallway and office environments. While the homing speed of robots using other approaches is constrained by the speed in the teaching phase, our robot is not bounded by such limit and can travel much faster without compromising the homing accuracy.

Bionic engineering has been a focus in the field of robotic researches. Inverse dynamic analysis is significant for the determination of dynamic parameters of bionic robots. The present paper uses a newly developed robot modular named Sambot to construct a caterpillar robotic mechanism, and designs a gait of trapezoidal wave locomotion for it. Two open-link models are put forth to simulate the dynamic behavior of such a locomotion. The inverse dynamic differential equations are derived by Kane's method and are then solved numerically by the Runge–Kutta method of the fourth order. Based on the numerical solutions of these differential equations, the applied joint torques required to produce the harmonic trapezoidal wave locomotion are determined finally, providing us important information on the gait control of the caterpillar robotic mechanism. Finally, the theoretical values of the joint torques are applied onto the present caterpillar mechanism to perform a locomotion experiment, which verifies the effectiveness of the present dynamics analysis.