This paper presents a novel global path planning method for mobile robots. An improved grid map, called three-dimensional-like map, is developed to represent the global workspace area. The new environment model includes not only contour information of obstacles but also artificial height information. Based on this new model, a simple but efficient obstacle avoidance algorithm is developed to solve robot path planning problems in static environment. The proposed algorithm only requires simple distance calculations and several comparison operations. In addition, unlike other algorithms, the proposed algorithm only needs to deal with some obstacles instead of all. The research results show that this method is computationally efficient and can be used to find an optimal or near optimal path.

Force-controlled series elastic actuators (SEAs) are the widely used components of novel physical human–robot interaction applications such as assistive and rehabilitation robotics. These systems are characterized by the presence of the “human in the loop” so that control response and stability depend on uncertain human dynamics. A common approach to guarantee stability is to use a passivity-based controller. Unfortunately, existing passivity-based controllers for SEAs do not define the performance of the force/torque loop. We propose a method to obtain predictable force/torque dynamics based on adaptive control and oversimplified human models. We propose a class of stable human-adaptive algorithms and experimentally show advantages of the proposed approach.

We present a model of construction using iterative amorphous depositions and give a distributed algorithm to reliably build ramps in unstructured environments. The relatively simple local strategy for interacting with irregularly shaped, partially built structures gives rise to robust adaptive global properties. We illustrate the algorithm in both single robot and multi-robot cases via simulations and describe how to solve key technical challenges to implementing this algorithm via a robotic prototype.

This paper focuses on practical application of a mobile manipulator by presenting the development and control of a two-wheel mobile robot with two arms called a balancing service robot (BSR) designated for indoor services. The mobile manipulator requires not only robust balancing position control but also force control to interact with objects. Movements with two wheels are controlled to satisfy stable balancing control for navigation and manipulation with two arms to perform given tasks. The robot is required to deal with external forces to maintain balance. The position-based impedance force control method (the admittance control) is utilized by filtering the force with the impedance function to react to the applied force from the operator. Experimental studies of navigation control under balancing condition and interacting control with a human operator are demonstrated. Experimental results confirm that the robot has smooth reaction against the disturbance induced by the applied external force.

Fall-related accidents are among the most serious concerns in elderly people, amputees and subjects with neurological disorders. The aim of this paper was to investigate the behaviour of healthy subjects wearing a novel light-weight pelvis exoskeleton controlled in zero-torque mode while carrying out unperturbed locomotion and managing unexpected perturbations. Results showed that the proposed exoskeleton was unobtrusive and had a minimum loading effect on the human biomechanics during unperturbed locomotion. Conversely, it affected the movement of the trailing leg while subjects managed unexpected slipping-like perturbations. These findings support further investigations on the potential use of powered exoskeletons to assist locomotion and, possibly prevent incipient falls.

This paper presents a whole-body dynamics controller for robust push recovery on a force-controlled bipedal robot. Featherstone's spatial vector method is used to deduce dynamics formulas. We reveal a relationship between the accelerations of the floating base and the desired external forces needed for those accelerations. Introducing constraints on the desired external forces causes corresponding constraints on the accelerations. Quadratic programming is applied to find the extremal accelerations, which recover the robot from pushes as best as possible. A robustness criterion is proposed based on the linear inverted pendulum model to evaluate the performance of push recovery methods quantitatively. We evaluate four typical push recovery methods and the results show that our method is more robust than these. The effectiveness of the proposed method is demonstrated by push recovery in simulations.

Due to the growing use of Atomic Force Microscope (AFM) nanorobots in the moving and manipulation of cylindrical nanoparticles (carbon nanotubes and nanowires) and the fact that these processes cannot be simultaneously observed, a computer simulation of the involved forces for the purpose of predicting the outcome of the process becomes highly important. So far, no dynamic 3D model that shows changes in these forces in the course of process implementation has been presented. An algorithm is used in this paper to show in 3D, the manner by which the dynamic forces vary in the mentioned process. The presented model can simulate the forces exerted on the probe tip during the manipulation process in three directions. Because of the nonlinearity of the presented dynamic model, the effective parameters have been also studied. To evaluate the results, the parameters of the 3D case (cylindrical model) are gradually reduced and it is transformed into a 2D model (disk model); and we can observe a good agreement between the results of the two simulations. Next, the simulation results are compared with the experimental results, indicating changes in lateral force. With the help of the offered dynamic model, the cantilever deformation and the forces interacting between probe tip and particle can be determined from the moment the probe tip contacts the nanoparticle to when the nanoparticle dislodges from the substrate surface.

In this paper, we study the visible trajectories planning for unmanned aerial vehicles (UAVs) modeled with a Dubins airplane in 3D urban environments. Our method is based on a fast and exact spatial visibility analysis of the 3D visibility problem from a viewpoint in 3D built-up environments. We consider the 3D urban environment buildings modeled as cubes (3D boxes) and present an analytic solution to the visibility problem. Based on an analytic solution, the algorithm computes the exact visible and hidden parts from a viewpoint in the urban environment. We present a local trajectory planner generating the most visible trajectory in a known 3D urban environment model, taking into account the dynamic and kinematic UAV constraints. The planner computes, at each time step, the next UAV's attainable velocities and explores the most visible node, while avoiding buildings as static obstacles in the environments, using the velocity obstacle method. The visibility type of the trajectory can be configured beforehand as visible roofs and surfaces in the environments. We demonstrate our visibility and trajectory planning method in simulations in several 3D urban environments, showing visible trajectory planning capabilities.

In this paper, the backstepping strategy is used to design an adaptive tracking controller for rigid-link electrically driven robots in the presence of parametric uncertainties in kinematics, manipulator dynamics, and actuator dynamics. To avoid acceleration measurements, two techniques are exploited. One technique adds compensation control terms to the control law signal. The other uses a linear in variable property of the Jacobian matrix. Global asymptotic convergence of the end-effector motion tracking errors is shown via Lyapunov analysis. Simulation results are presented to show the effectiveness of the proposed control scheme.

The tip of a flexible needle with a bevel tip approximately follows a planar arc when it is inserted into soft tissue only with the force applied to the needle along the needle axis. The direction of the arc can be controlled by the rotation input around the needle axis. This flexible and steerable needle has been shown to have a considerable potential in clinical applications due to its maneuverability and steerability. Beyond the needle insertion to a single destination, this paper concerns obtaining needle trajectories that reach multiple targets. Specifically, we propose an algorithm for the insertion of a flexible needle to travel from a single insertion point (i.e. port) to multiple targets. The insertion is motivated by the observation that multiple targets can be reached by the flexible needle through a combination of insertion, partial retraction, turning, and reinsertion of the flexible needle. In this paper we develop an insertion algorithm that minimizes tissue damage during the needle insertion to multiple targets. To this end, a cost function which computes the length of needle trajectory that can be thought of as the tissue damage is defined, and is minimized. Through the minimization, we find the optimal insertion parameters such as the port location, the insertion direction at the port, the targeting order, the turning angles, and the lengths of forward insertions and retractions. To reduce the computation time, we perform workspace analysis for this approach to filter out the no-solution cases. We present numerical examples of the simulated needle insertion for multiple targets with and without obstacles and show the benefit of the proposed method in terms of the tissue damage and the number of skin punctures. Extensions of the proposed approach to more complex cases such as more than three target points and maneuvering around spherical obstacles are also discussed.

This paper focuses on behavior recognition in an underwater application as a substitute for communicating through acoustic transmissions, which can be unreliable. The importance of this work is that sensor information regarding other agents can be leveraged to perform behavior recognition, which is activity recognition of robots performing specific programmed behaviors, and task-assignment. This work illustrates the use of Behavior Histograms, Hidden Markov Models (HMMs), and Conditional Random Fields (CRFs) to perform behavior recognition. We present challenges associated with using each behavior recognition technique along with results on individually selected test trajectories, from simulated and real sonar data, and real-time recognition through a simulated mission.

One of the main challenges in robotics is navigating autonomously through large, unknown, and unstructured environments. Simultaneous localization and mapping (SLAM) is currently regarded as a viable solution for this problem. As the traditional metric approach to SLAM is experiencing computational difficulties when exploring large areas, increasing attention is being paid to topological SLAM, which is bound to provide sufficiently accurate location estimates, while being significantly less computationally demanding. This paper intends to provide an introductory overview of the most prominent techniques that have been applied to topological SLAM in terms of feature detection, map matching, and map fusion.

A widely used method for pose estimation in mobile robots is odometry. Odometry allows the robot in real time to reconstruct its position and orientation from the wheels' encoder measurements. Given to its unbounded nature, odometry calculation accumulates errors with quadratic increase of error variance with traversed distance. This paper develops a novel method for odometry calibration and error propagation identification for mobile robots. The proposed method uses a laser-based interferometer to measure distance precisely. Two variants of the proposed calibration method are examined: the two-parameter model and the three-parameter model. Experimental results obtained using a Khepera 3 mobile robot showed that both methods significantly increase accuracy of the pose estimation, validating the effectiveness of the proposed calibration method.

It is common in robot tracking control that controllers are designed based on the exact kinematic model of the robot manipulator. However, because of measurement errors and changes of states in practice, the original kinematic model is often no longer accurate and will degrade the control result. An adaptive backstepping controller is designed here for parallel robot systems with kinematics and dynamics uncertainties. Backstepping control is used to manage the transformation between the errors in task space and joint space. Adaptive control is utilized to compensate for uncertainties in both dynamics and kinematics. The controller demonstrated good performance in simulation.

This paper focuses on the mechanism design of a slide-block structure and its application on a biomimetic modular robotic fish for three-dimensional swimming. First, as a barycenter-adjustor, the slide-block structure is integrated into a mechanical design of a robotic fish, which is constructed by a control module, a driving module, and a fan-shaped caudal fin. The three-dimensional locomotion of robotic fish is decomposed into two-dimensional locomotion in horizontal plane and ascent–descent locomotion in vertical plane. Both the kinematics of the horizontal swim and the dynamics of the ascent–descent swim are analyzed by the curve fitting method. Finally, experimental results validate the three-dimensional swimming capability of the robotic fish. Furthermore, the impact of two design parameters on the swimming capability of the robotic fish is discussed by the experimental method. The experimental results confirm that the robotic fish with one driving module and a fan-shaped low-aspect-ratio caudal foil can produce higher propulsive speed than other parameter combinations.

Beginning with a deterministic distributed feedback control for nonholonomic vehicle formations, we develop a stochastic optimal control approach for agents to enhance their non-optimal controls with additive correction terms based on the Hamilton–Jacobi–Bellman equation, making them optimal and robust to uncertainties. In order to avoid discretization of the high-dimensional cost-to-go function, we exploit the stochasticity of the distributed nature of the problem to develop an equivalent Kalman smoothing problem in a continuous state space using a path integral representation. Our approach is illustrated by numerical examples in which agents achieve a formation with their neighbors using only local observations.

In this study, kinematic analysis of 6-DOF RSS parallel manipulator using Denavit Hartenbeng (D-H) method is investigated. In addition, in order to improve the proposed method, determination of all the active and passive angles, required to obtain Jacobian and complete dynamic model of manipulator, is also achieved. The effects of dynamic models of 6-DOF RSS parallel manipulator with its actuators on trajectory tracking control are studied in detail. Feedback dynamic compensation terms of motor-mechanism coupling system that is needed to compute torque control are obtained through both a single link approximation model and a complete dynamic model. The complete model is derived by taking account of the interaction between the input links and coupler links of the manipulator. Simulations showed that obtaining complete model of manipulator by means of D-H method and using computed control law could improve the quality of trajectory tracking control of parallel manipulator.

Changes in world-wide population trends have provided new demands for new technologies in areas such as care and rehabilitation. Recent developments in the the field of robotics for neurorehabilitation have shown a range of evidence regarding usefulness of these technologies as a tool to augment traditional physiotherapy. Part of the appeal for these technologies is the possibility to place a rehabilitative tool in one's home, providing a chance for more frequent and accessible technologies for empowering individuals to be in charge of their therapy.

Objective: this manuscript introduces the Supervised Care and Rehabilitation Involving Personal Tele-robotics (SCRIPT) project. The main goal is to demonstrate design and development steps involved in a complex intervention, while examining feasibility of using an instrumented orthotic device for home-based rehabilitation after stroke.

Methods: the project uses a user-centred design methodology to develop a hand/wrist rehabilitation device for home-based therapy after stroke. The patient benefits from a dedicated user interface that allows them to receive feedback on exercise as well as communicating with the health-care professional. The health-care professional is able to use a dedicated interface to send/receive communications and remote-manage patient's exercise routine using provided performance benchmarks. Patients were involved in a feasibility study (n=23) and were instructed to use the device and its interactive games for 180 min per week, around 30 min per day, for a period of 6 weeks, with a 2-months follow up. At the time of this study, only 12 of these patients have finished their 6 weeks trial plus 2 months follow up evaluation.

Results: with the “use feasibility” as objective, our results indicate 2 patients dropping out due to technical difficulty or lack of personal interests to continue. Our frequency of use results indicate that on average, patients used the SCRIPT1 device around 14 min of self-administered therapy a day. The group average for the system usability scale was around 69% supporting system usability.

Conclusions: based on the preliminary results, it is evident that stroke patients were able to use the system in their homes. An average of 14 min a day engagement mediated via three interactive games is promising, given the chronic stage of stroke. During the 2nd year of the project, 6 additional games with more functional relevance in their interaction have been designed to allow for a more variant context for interaction with the system, thus hoping to positively influence the exercise duration. The system usability was tested and provided supporting evidence for this parameter. Additional improvements to the system are planned based on formative feedback throughout the project and during the evaluations. These include a new orthosis that allows a more active control of the amount of assistance and resistance provided, thus aiming to provide a more challenging interaction.

This paper presents a novel one-degree-of-freedom (1-DOF) single-loop reconfigurable 7R mechanism with multiple operation modes (SLR7RMMOM), composed of seven revolute (R) joints, via adding a revolute joint to the overconstrained Sarrus linkage. The SLR7RMMOM can switch from one operation mode to another without disconnection and reassembly, and is a non-overconstrained mechanism. The algorithm for the inverse kinematics of the serial 6R mechanism using kinematic mapping is adopted to deal with the kinematic analysis of the SLR7RMMOM. First, a numerical method is applied and an example is given to show that there are 13 sets of solutions for the SLR7RMMOM, corresponding to each input angle. Among these solutions, nine sets are real solutions, which are verified using both a computer-aided design (CAD) model and a prototype of the mechanism. Then an algebraic approach is also used to analyse the mechanism and same results are obtained as the numerical one. It is shown from both numerical and algebraic approaches that the SLR7RMMOM has three operation modes: a translational mode and two 1-DOF planar modes. The transitional configurations among the three modes are also identified.