This paper presents a new approach to the management of the environmental map for mobile robots in dynamic environments. The environmental map is built of primitive features, such as lines, points, and even circles, extracted from ambiguous data captured by the robot's sonar sensor ring. The feature map must be managed because the indoor surroundings where mobile robots operate are continuously changing due to nonstationary objects, such as wastebaskets, tables, and people. The features are processed by trimming, division, or removal, depending on the dynamic circumstances. All processing refers to the occupancy probabilities of grid squares generated for the map features. The occupancy probabilities of the squares are updated using the Bayesian updating model with the sonar sensor data. Experimental results demonstrate the validity of the proposed method.

Exponentially stabilizing a non-Spring Loaded Inverted Pendulum (SLIP) model-based one-legged hopping robot in stance phase is studied. Differing from the SLIP model systems, the hopping robot with non-SLIP model considered in this paper does not restrict the center of mass of the robot coinciding to the hip joint. A specific underactuated one-legged hopping robot with two actuated arms are selected to investigate the dynamics and control problem. It is shown that the system holds the essential nonlinear prosperities of general systems and belongs to a class of second-order nonholonomic mechanical systems, which cannot be stabilized by any smooth time-invariant state feedback. By using a coordinates transform based on the so-called normalized momentum, a robust backstepping control method is presented for the specific hopping robot system. Both theoretical analysis and numerical simulations show that the robust backstepping controller can stabilize the underactuated one-legged hopping robot to its balance configuration as well as a periodic motion trajectory near to the balance configuration. These results are significative for designing a new non-SLIP model based hopping robot systems with more biological characteristics.

Suturing and tying knots assisted by surgical robot systems are complicated and time-consuming tasks in minimally invasive surgery (MIS). It is almost impossible to perform these operations in laryngeal MIS because motions of the end-effectors are greatly confined by a narrow and long laryngoscope tube. This paper presents the robot-assisted operations of suturing and knot-tying in a laryngeal surgery under a self-retaining laryngoscope, which has a greatly confined workspace. In order to use robot assistance to perform the suturing and knot-tying tasks in such a workspace, an appropriate suturing path is planned. The suturing path planning is completed based on a knot-tying algorithm called the bending-twisting knot-tying (BTKT). A robot system for laryngeal MIS called MicroHand III is designed. The kinematical model of the system is developed in the paper. The simulation and experimental results have shown that suturing and knot-tying assisted by MicroHand III system are successful.

In this work a new nonoverconstrained redundant decoupled robot, free of compound joints, formed from three parallel manipulators, with two moving platforms and provided with six active limbs connected to the fixed platform, called LinceJJP, is presented. Interesting applications such as multi-axis machine tools with parallel kinematic architectures, solar panels, radar antennas, and telescopes are available for this novel spatial mechanism.

The common serial robot or parallel robot is difficult to implement for CT-guided surgery in a limited workspace. A novel hybrid robot with 9 degrees of freedom is presented in this paper, whose detailed structure is analysed based on screw theory and displacement manifold (DM). The dexterity of the hybrid robot is provided in terms of Riemann manifold (RM). Besides, DICOM (digital imaging communications in medicine) image processing, spatial registration and 3D dynamic reconstruction in the operation planning subsystem are analysed, in which some innovative methods are introduced. Meanwhile, the architecture of the CT-guided hybrid robot system and its subsystems are proposed. Simulative clinical experiment showed that the locating precision of the hybrid robot reaches 1.08 mm, which can meet the requirement of CT-guided surgery.

The uncalibrated robotic hand–eye coordination problem is firstly modeled by a dynamic system, where the unknown hand–eye relationship is regarded as the system's unmodeled dynamics. A state observer is then designed to estimate impacts of this modeling error together with the system's external disturbances. With the estimation results as the compensation, the system control is thus accomplished based on a nonlinear combination of the system state errors. Convergence analysis of the whole system under the proposed control scheme is emphasized. Simulations and experiment results are presented to verify the performance of the proposed approach.

In this work, we present a continuous observer and continuous controller for a multiple degree of freedom robot manipulator with hysteretic joint friction. The fictitious hysteresis state is of course unknown to the controller and must be estimated. The joint velocities are assumed measured here. For this considered plant, we propose and present a continuous observer/controller that estimates or observes the hysteresis state and drives the position tracking error to zero. We prove that the combined tracking error and observer error converges to zero globally exponentially.

This paper deals with the design, implementation, and performance evaluation of a new type of 4-DOF parallel mechanism providing three translations and one rotation for high-speed handling and machining. This parallel mechanism is named H4. A necessary condition and system configuration of the H4 are also described. Hardware and kinematics of the H4 is addressed and the manipulability ellipsoid which is one of the widely used methods to examine the design of parallel mechanisms is addressed. The performance evaluation is carried out to demonstrate the H4 robot. The simulation and experimental results show that three different controllers, the PD, PD + velocity feed-forward, and dynamic compensation controller, dramatically improve the trajectory tracking accuracy.

This paper describes a new approach for estimating the vehicle motion trajectory in complex urban environments by means of visual odometry. A new strategy for robust feature extraction and data post-processing is developed and tested on-road. Images from scale-invariant feature transform (SIFT) features are used in order to cope with the complexity of urban environments. The obtained results are discussed and compared to previous works. In the prototype system, the ego-motion of the vehicle is computed using a stereo-vision system mounted next to the rear view mirror of the car. Feature points are matched between pairs of frames and linked into 3D trajectories. The distance between estimations is dynamically adapted based on re-projection and estimation errors. Vehicle motion is estimated using the non-linear, photogrametric approach based on RAndom SAmple Consensus (RANSAC). The final goal is to provide on-board driver assistance in navigation tasks, or to provide a means of autonomously navigating a vehicle. The method has been tested in real traffic conditions without using prior knowledge about the scene or the vehicle motion. An example of how to estimate a vehicle's trajectory is provided along with suggestions for possible further improvement of the proposed odometry algorithm.

Sound source tracking is an important function for autonomous robots, because sound is omni-directional and can be recognized in dark environment. This paper presents a new approach to sound source tracking for mobile robots using auditory sensors. We consider a general type of two-wheeled mobile robot that has wide industrial applications. Because obstacle avoidance is also an indispensable function for autonomous mobile robots, the robot is equipped with distance sensors to detect obstacles in real time. To deal with the robot's nonholonomic constraint and combine information from the auditory and distance sensors, we propose a model reference control approach in which the robot follows a desired trajectory generated by a reference model. The effectiveness of the proposed method is confirmed by experiments in which the robot is expected to approach a sound source while avoiding obstacles.

This paper describes a vehicle detection system based on support vector machine (SVM) and monocular vision. The final goal is to provide vehicle-to-vehicle time gap for automatic cruise control (ACC) applications in the framework of intelligent transportation systems (ITS). The challenge is to use a single camera as input, in order to achieve a low cost final system that meets the requirements needed to undertake serial production in automotive industry. The basic feature of the detected objects are first located in the image using vision and then combined with a SVM-based classifier. An intelligent learning approach is proposed in order to better deal with objects variability, illumination conditions, partial occlusions and rotations. A large database containing thousands of object examples extracted from real road scenes has been created for learning purposes. The classifier is trained using SVM in order to be able to classify vehicles, including trucks. In addition, the vehicle detection system described in this paper provides early detection of passing cars and assigns lane to target vehicles. In the paper, we present and discuss the results achieved up to date in real traffic conditions.

A CCC limb and a new 3CCC parallel mechanism have been designed in this paper based on geometry analysis. Their mobility and geometrical constraints are discussed by using screw theory and geometrical equations separately. Following that both the inverse and forward kinematics of the 3CCC parallel mechanism are proposed, in which Dixon's resultant is used to get the forward solutions for the orientation and a eighth-order polynomial equation in one unknown is obtained, leading to the results for the position analysis, numerical examples confirm these theoretical results. A short comparison with the traditional Stewart platforms is presented in terms of kinematics, workspace and trajectory planning.

This paper presents the requirements, design criteria and methodology used to develop the design of a new self-contained prosthetic hand to be used by transradial amputees. The design is based on users' needs, on authors background and knowledge of the state of the art, and feasible fabrication technology with the aim of replicating as much as possible the functionality of the human hand. The paper focuses on the design approach and methodology which is divided into three steps: (i) the mechanical actuation units, design and actuation distribution; (ii) the mechatronic development and finally (iii) the controller architecture design. The design is presented here and compared with significant commercial devices and research prototypes.

The effect of axial forces on the dynamic properties is formulated and investigated for a 3-PRR planar parallel manipulator with three flexible intermediate links. A dynamic model of the manipulator system is developed based on the assumed mode method with the consideration of the effect of longitudinal forces on lateral stiffness is included. The flexible intermediate links are modeled as Euler–Bernoulli beams with pinned-pinned boundary conditions, which are verified by experimental modal tests. Natural frequencies of bending vibration of the intermediate links are derived as the functions of axial force and rigid-body motion of the manipulator. Dynamic behavior including the effect of axial forces on lateral deformation is investigated, and configuration-dependant frequencies are analyzed. Numerical simulations of configuration-dependent frequency properties and axial forces are performed to illustrate the effect of axial forces on the dynamic behaviors of the flexible parallel manipulator. Simulation results of mode amplitudes, deformations, axial forces, inertial, and coupling forces are presented, and further validate the theoretical derivations. These analyses and results provide a new and valuable insight to the design and control of the parallel manipulators with flexible intermediate links.

Hull cleaning before repainting is a key operation in the maintenance of ships. For more than a decade, a means to improve this operation has been sought through robotization and the use of different techniques such as grit blasting and ultra high pressure water jetting. Despite this, it continues to be standard practice in shipyards that this process is carried out manually. This paper presents a family of robots that aims to offer important improvements to the process as well as satisfying, to a great extent, all the operative requirements of efficiency, security, and respect for the environment that shipyards nowadays demand. It is described the family of devices with emphasis on the mechanical design. This set consists of two vertical robotic towers and a robot climber. In addition, it is shown the control architecture of the global system. Finally, operative results are presented together with a comparison between the performance achieved in shipyards through the use of these robots and those obtained with a manual process.

This paper presents the development and testing of a haptic interface compatible with a functional magnetic resonance imaging (fMRI) environment for neuroscience human motor control studies. A carbon fiber extension enables us to use the widely accepted and available haptic device Phantom 1.5.

In the first part of the paper development of the mechanical extension together with its kinematic and dynamic models are presented. The second part is focused on testing of the extended haptic interface. The experiment's results both inside and outside the fMRI environment are presented. Tests outside a scanner have shown that the mechanical extension has no notable effect on a subject performance. Experiments with the scanner have confirmed electromagnetic compatibility of the extended haptic system.

At the end it is concluded that the extended haptic device is fully compatible with the fMRI environment, and a virtual environment task that will allow neuroscientists to study a human motor control is proposed.

In this paper, an application is presented of a cable-based parallel manipulator as measuring system for an experimental identification of human walking characteristics. Experimental results have been obtained by means of a new version of CaTraSys (Cassino Tracking System), which is a measuring system that has been designed and built at Laboratory of Robotics and Mechatronics (LARM) in Cassino, Italy. The new version of the CaTraSys system has been used to determine the trajectory of the human limb extremity during walking operation and furthermore the system is able to measure forces that are exerted by a limb. Experimental determination of articulation mobility is also presented with numerical and experimental results.

In our previous work, a random-sampling-based footstep planner has been proposed for global biped navigation. Goal-probability threshold (GPT) is the key parameter that controls the convergence rate of the goal-biased nonuniform sampling in the planner. In this paper, an approach to optimized GPT adaptation is explained by a benchmarking planning problem. We first construct a benchmarking model, in which the biped navigation problem is described in selected parameters, to study the relationship between these parameters and the optimized GPT. Then, a back-propagation (BP) neural network is employed to fit this relationship. With a trained BP neural network modular, the optimized GPT can be automatically generated according to the specifications of a planning problem. Compared with previous methods of manual and empirical tuning of GPT for individual planning problems, the proposed approach is self-adaptive. Numerical experiments verified the performance of the proposed approach and furthermore showed that planning with BP-generated GPTs is more stable. Besides the implementation in specific parameterized environments studied in this paper, we attempt to provide the frame of the proposed approach as a reference for footstep planning in other environments.

Biomimetic applications play an important role in informing the field of robotics. One aspect is navigation – a skill automobile robots require to perform useful tasks. A sub-area of this is search strategies, e.g. for search and rescue, demining, exploring surfaces of other planets or as a default strategy when other navigation mechanisms fail. Despite that, only a few approaches have been made to transfer biological knowledge of search mechanisms on surfaces along the ground into biomimetic applications. To provide insight for robot navigation strategies, this study describes the paths a crayfish used to explore terrain. We tracked movement when different sets of sensory input were available. We then tested this algorithm with a computer model crayfish and concluded that the movement of C. destructor has a specialised walking strategy that could provide a suitable baseline algorithm for autonomous mobile robots during navigation.

This paper presents a control strategy for surgical interventions, applied on a human–robot cooperative system, which facilitates the sharing of responsibilities between surgeon and robot. The controller utilizes virtual fixtures to constrain the movements of the end-effector into a predefined path or region. Possible deviation error can be compensated in two different ways: (a) manual compensation and (b) autonomous compensation. With manual compensation, the system defines both virtual fixtures and error compensation directions, but the surgeon must apply manual forces himself/herself in order to generate end-effector motion. With autonomous compensation, a clear distribution of responsibilities between surgeon and robotic system is present, meaning the surgeon has complete control of the end-effector along the preferred directions, while the robot autonomously compensates for any deviation along the non-preferred directions.