This paper investigates 3-dimensional (3D) Simultaneous Localization and Mapping (SLAM) and the corresponding observability analysis by fusing data from landmark sensors and a strap-down Inertial Measurement Unit (IMU) in an adaptive Kalman filter (KF). In addition to the vehicle's states and landmark positions, the self-tuning filter estimates the IMU calibration parameters as well as the covariance of the measurement noise. The discrete-time covariance matrix of the process noise, the state transition matrix and the observation sensitivity matrix are derived in closed form, making it suitable for real-time implementation. Examination of the observability of the 3D SLAM system leads to the the conclusion that the system remains observable, provided that at least three known landmarks, which are not placed in a straight line, are observed.

This paper presents a numerical algorithm to model the impact between articulated structures, or between an articulated structure and an object. The proposed algorithm, called impulse articulated-body algorithm (IABA), is based on the ABA but uses impulses and velocities rather than forces and accelerations. The algorithm also inherits the advantages of the ABA: versatility and low computational cost. The IABA provides a method to determine the impact impulse, without increasing the order of the algorithm.

Consider a robot trying to accomplish a mission in an unfamiliar, hostile, and dynamic environment. As the robot encounters a seemingly insurmountable obstacle, it quickly reconfigures itself into two smaller robots, and with the aid of a nearby puddle of water, these two robots conduct self-detection procedures to confirm successful reconfiguration. One robot then calibrates itself using its reduced sensor suite and begins climbing over the obstacle, whilst the other robot folds itself into a compact structure and finds a crevice it can use to bypass the obstacle. But when the obstacle shifts, both robots send signals to a base to warn of impending mission failure. A copy of the original robot, located at the base, receives these warning signals and initiates a rapid self-replication process by assembling available resources. The resultant robotic offspring are then ready to continue the mission when called upon.

In this paper, accuracy and stiffness analysis of a 3-RRP spherical parallel manipulator (SPM) (Enferadi and Tootoonchi, A novel spherical parallel manipulator: Forward position problem, singularity analysis and isotropy design, Robotica, vol. 27, 2009, pp. 663–676) with symmetrical geometry is investigated. At first, the 3-RRP SPM is introduced and its inverse kinematics analysis is performed. Isotropic design, because of its design superiority, is selected and workspace of the manipulator is obtained. The kinematics conditioning index (KCI) is evaluated on the workspace. Global conditioning index (GCI) of the manipulator is calculated and compared with another SPM. Unlike traditional stiffness analysis, the moving platform is assumed to be flexible. A continuous method is used for obtaining mathematical model of the manipulator stiffness matrix. This method is based on strain energy and Castigliano's theorem. The mathematical model is verified by finite element model. Finally, using mathematical model, kinematics stiffness index (KSI), and global stiffness index (GSI) are evaluated.

A novel approach for trajectory tracking of a mobile-robots formation by using linear algebra theory and numerical methods is presented in this paper. The formation controller design is based on the formation states concept and the dynamic model of a unicycle-like nonholonomic mobile robot. The proposed control law designed is decentralized and scalable. Simulations and experimental results confirm the feasibility and the effectiveness of the proposed controller and the advantages of using the dynamic model of the mobile robot. By using this new strategy, the formation of mobile robots is able to change its configuration (shape and size) and follow different trajectories in a precise way, minimizing the tracking and formation errors.

This paper presents a module for pedestrian detection from a moving vehicle in low-light conditions. The algorithm make use of a single far infrared camera based on a microbolometer. Images of the area ahead of the vehicle are analyzed to determine if any pedestrian might be in its trajectory. Detection is achieved by searching for distributions of temperatures in the scene similar to that of the human body. Those areas with an appropriate temperature, size, and position in the image are classified, by means of a correlation between them and some probabilistic models, which represents the average temperature of the different parts of the human body. Finally, those pedestrians found are tracked in a subsequent step, using an unscented Kalman filter. This final stage of the algorithm enables the algorithm to predict the trajectory of the pedestrian, in a way that does not depend on the movement of the camera. The aim of this system is to warn the vehicle's driver and reduce the reaction time in case an emergency break is necessary.

The force analysis of parallel manipulators is one of the important issues for mechanical design and control, but it is quite difficult often because of the excessive unknowns. A new approach using screw theory for a 3-RPS parallel mechanism is proposed in this paper. It is able to markedly reduce the number of unknowns and even make the number of simultaneous equations to solve not more than six each time, which may be called force decoupling. With this method, first the main-pair reactions need to be solved for, and then, the active forces and constraint reactions of all other kinematic pairs can be simultaneously obtained by analyzing the equilibrium of each body one by one. Finally, a numerical example and a discussion are given.

Achieving energy-efficient and high-speed dynamic walking has become one of the main subjects of research in the area of robotic biped locomotion, and passive dynamic walking has attracted a great deal of attention as a solution to this. It is empirically known that the convex curve of the foot, which characterizes passive–dynamic walkers, has an important effect on increasing the walking speed.

This paper mainly discusses our investigations into the driving mechanism for compass-like biped robots and the rolling effect of semicircular feet. We first analyze the mechanism for a planar fully actuated compass-like biped model to clarify the importance of ankle-joint torque by introducing a generalized virtual-gravity concept. A planar underactuated biped model with semicircular feet is then introduced and we demonstrate that virtual passive dynamic walking only by hip-joint torque can be accomplished based on the rolling effect. We then compare the rolling effect with a flat feet model through linear approximation, and show that the rolling effect is equivalent to virtual ankle-joint torque. Throughout this paper, we provide novel insights into how zero-moment-point-free robots can generate a dynamic bipedal gait.

This work is concerned with trajectory tracking of robots when the electrical dynamics of the brushless DC motor actuators is considered. It is shown that proportional-derivative (PD) control with feedforward compensation, plus some additional terms to cope with the electrical dynamics, ensures state boundedness. Furthermore, tracking error converges to zero from arbitrarily large initial conditions if controller gains are correctly chosen. Under mild assumptions, this controller reduces to the well-known PD control with feedforward compensation when implemented according to torque control, a successful industrial practice. Thus, it is explained, for the first time, why this strategy works well in applications.

The stiffness modeling and elastic deformation of 3 degrees of freedom, 3-universal joints–prismatic pairs–universal joints (UPU) parallel manipulator (PM) with one translation and two rotations are studied. First, the constraint wrenches are derived corresponding to the special orientation of universal joints in each of the UPU legs. Second, the elastic deformation of active legs produced by these active forces and constrained wrenches are derived. Third, a 6 × 6 Jacobian matrix is derived from constraint and active forces, and the statics is solved. Finally, the stiffness matrix of 3-UPU PM is established and its elastic deformation is solved.

The behavior of mechanical manipulators with backlash is analyzed. In order to acquire and study the signals an experimental setup is implemented. The signal processing capabilities of the wavelets are used for de-noising the experimental signals and the energy of the obtained components is analyzed. To evaluate the backlash effect upon the robotic system, it is proposed an index based on the pseudo phase plane representation. Several tests are developed that demonstrate the coherence of the results.

This paper addresses the problem of self-detection by a robot. The paper describes a methodology for autonomous learning of the characteristic delay between motor commands (efferent signals) and observed movements of visual stimuli (afferent signals). The robot estimates its own efferent-afferent delay from self-observation data gathered while performing motor babbling, i.e., random rhythmic movements similar to the primary circular reactions described by Piaget. After the efferent-afferent delay is estimated, the robot imprints on that delay and can later use it to successfully classify visual stimuli as either “self” or “other.” Results from robot experiments performed in environments with increasing degrees of difficulty are reported.

In this paper we study the problem of passive walking for a compass-gait biped with gait asymmetries. In particular, we identify and classify bifurcations leading to chaos caused by the gait asymmetries because of unequal leg masses. We present bifurcation diagrams showing step period versus the ratio of leg masses at various walking slopes. The cell mapping method is used to find stable limit cycles as the parameters are varied. It is found that a variety of bifurcation diagrams can be grouped into six stages that consist of three expanding and three contracting stages. The analysis of each stage shows that marginally stable limit cycles exhibit period-doubling, period-remerging, and saddle-node bifurcations. We also show qualitative changes regarding chaos, i.e., generation and extinction of chaos follow cyclic patterns in passive dynamic walking.

This paper investigates the stable-running problem of a planar underactuated biped robot, which has two springy telescopic legs and one actuated joint in the hip. After modeling the robot as a hybrid system with multiple continuous state spaces, a natural passive limit cycle, which preserves the system energy at touchdown, is found using the method of Poincaré shooting. It is then checked that the passive limit cycle is not stable. To stabilize the passive limit cycle, an event-based feedback control law is proposed, and also to enlarge the basin of attraction, an additive passivity-based control term is introduced only in the stance phase. The validity of our control strategies is illustrated by a series of numerical simulations.

This study offers the solution of the end-effector trajectory tracking problem subject to state constraints, suitably transformed into control-dependent ones, for mobile manipulators. Based on the Lyapunov stability theory, a class of controllers fulfilling the above constraints and generating the mobile manipulator trajectory with (instantaneous) minimal energy, is proposed. The problem of manipulability enforcement is solved here based on an exterior penalty function approach which results in continuous mobile manipulator controls even near boundaries of state constraints. The numerical simulation results carried out for a mobile manipulator consisting of a non-holonomic unicycle and a holonomic manipulator of two revolute kinematic pairs, operating in a two-dimensional task space, illustrate the performance of the proposed controllers.

Psychophysiological measurements, which serve as objective indicators of psychological state, have recently been introduced into human–robot interaction. However, their usefulness in haptic interaction is uncertain, since they are influenced by physical workload. This study analyses psychophysiological responses to a haptic task with three different difficulty levels and two different levels of physical load. Four physiological responses were recorded: heart rate, skin conductance, respiratory rate and skin temperature. Results show that mean respiratory rate, respiratory rate variability and skin temperature show significant differences between difficulty levels regardless of physical load and can be used to estimate cognitive workload in haptic interaction.

When generating gaits for soft robots (those with no explicit joints), it is not evident that undulating control schemes are the most efficient. In considering alternative control schemes, however, the computational costs of evaluating continuum mechanic models of soft robots represent a significant bottleneck. We consider the use of lumped dynamic models for soft robotic systems. Such models have not been employed previously to design gaits for soft robotic systems, though they are widely used to simulate robots with compliant joints. A major question is whether these methods are accurate enough to be representations of soft robots to enable gait design and optimization. This paper addresses the potential “reality gap” between simulation and experiment for the particular case of a soft caterpillar-like robot. Experiments with a prototype soft crawler demonstrate that the lumped dynamic model can capture essential soft-robot mechanics well enough to enable gait optimization. Significantly, experiments verified that a prototype robot achieved high performance for control patterns optimized in simulation and dramatically reduced performance for gait parameters perturbed from their optimized values.

High accuracy is usually difficult to obtain with a robotic arm installed on a mobile base, since the errors of the base are transferred to the manipulator. This paper proposes a method to address this problem through integration of a self-calibration algorithm and low-cost sensors. The self-calibration algorithm might be repeated several times during execution of a mission by the robot and is only based on the internal sensors of the robot, meaning that external observers or reference point transceivers (e.g., ultrasonic transceivers) are not used. The proposed self-calibration system was implemented on a pole climbing robot and effectively improved the positioning accuracy of the climbing arm.

This paper deals with iterative learning control (ILC) design to solve the trajectory tracking problem for rigid robot manipulators subject to external disturbances, and performing repetitive tasks. A D-type ILC is presented with an initial condition algorithm, which gives the initial state value in each iteration automatically. Thus, the resetting condition (the initial state error is equal to zero) is not required. The λ-norm is adopted as the topological measure in our proof of the asymptotic stability of this control scheme, over the whole finite time-interval, when the iteration number tends to infinity. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.

A new type of 28-DOF (degree of freedom) full-size humanoid robot, driven by a closed-chain type of joint actuation system, is developed in this paper. Each leg of the robot is composed of six joints, where three are at the hip, one is at the knee, and two are at the ankle. The robot has six joints for each arm, one balancing joint, and three joints for the head, with two cameras. The weight of the robot is 75 kg, and its height is 168 cm.

The actuation systems of the pitching joint for the arms and legs of the robot are designed based on a closed-chain mechanism composed of four bar links driven by a ball screw, and each leg of the robot is designed to support 95 kg weight to include a 20 kg payload that can be carried by the robot arms having very light designs (with weight 8.5 kg), but each capable of carrying a 10 kg payload.

An analysis of the closed-chain joint actuation systems of a light arm capable of handling heavy objects is performed, and the light arm is designed via finite-element method analysis performed using ANSYS. In addition, the kinematic analysis and the detailed structure of the arm and leg of the robot are performed.

The main controller uses the ARM processor and a distributed controller for the leg joints is developed using the TMS320c2407 processor with the communications between the main and joint controllers being performed via the CAN system.

Good performances of the proposed robot is demonstrated by presenting several experimental results; these include (1) experimentally handling a 13 kg payload, (2) through walking experiments of the robot supporting a 85 kg load, and (3) measurements of the arm and leg joint motors while performing walking experiments.