We present a novel framework for collision free assisted navigation of a semi-autonomous vehicle in complex unknown environments with moving and steady obstacles. In the proposed system, a semi-autonomous vehicle is guided by a human operator and an automatic reactive navigator. The autonomous reactive navigation block takes control from the human operator in situations where there is the danger of collision with obstacle. A mathematically rigorous analysis of the proposed approach is provided. The performance of the proposed assisted navigation system is demonstrated via experiments with a real semi-autonomous hospital bed and extensive computer simulations.

In this paper, a closed-form dynamic model of flexible manipulators is developed, based on the Newton–Euler formulation of motion equations of flexible links and on the adoption of the spatial vector notation. The proposed model accounts for two main innovations with respect to the state of the art: it is obtained in closed form with respect to the joints and modal coordinates (including the quadratic velocity terms) and motion equations of the whole manipulator can be computed for any arbitrary shape of the links and any possible link cardinality starting from the output of several commercial (finite element analysis) FEA codes. The Newton–Euler formulation of motion equations in terms of the joint and elastic variables greatly improves the simulation performances and makes the model suitable for real-time control and active vibration damping. The model has been compared with literature benchmarks obtained by the classical multibody approach and further validated by comparison with experiments collected on an experimental manipulator.

In order to potentially realize the advantages of planar parallel manipulators to be used for hybrid machine tools, the inherently abundant singularities which diminish the usable workspace must be eliminated. Proper structure synthesis and dimensional synthesis can provide a good solution. So, a non-conventional architecture of a three-PPR planar parallel manipulator is proposed in this paper for a hybrid machine tool. The proposed architecture permits a large dexterous workspace with unlimited orientation capability and no singularities. It also provides partially decoupled motion which permits independent actuators control. The kinematic, singularity, orientation capability and workspace analyses of the proposed manipulator are studied to verify those advantages. Based on a non-dimensional design parameter space, the highly important indices for this application namely the workspace index (WI), the motion/force transmission index, the kinematic and dynamic dexterity indices and the stiffness index are selected to be maximized yielding proper dimensions of the design parameters. Those performance indices are proven to be uniform over all the workspace achieving highly important characteristics of uniform accuracy, acceleration characteristics, rigidity and force transmissibility. Performance evaluation is finally presented to verify the high performance of the proposed non-singular planar parallel manipulator with high orientation capability.

Energy expenditure (EE) is an important criterion for design and control of biped walking robots. However, the cause-effect analyses enabled by total EE, which is lumped over a time duration and all system degrees-of-freedom (DOFs), are limited. In this study, robotic gait energetics is evaluated through a DOF-based instrumentation system designed for instantaneous evaluation of bidirectional current and applied voltage at each joint actuator. The instrumentation system includes a dual-module arrangement of buffers and attenuators, and accommodates and synchronizes the voltage and current measurements from multiple actuators. For illustrative purposes, this system is implemented at each DC servomotor in a biped robot, DARwIn-OP, to analyze the electrical EE rates for walking at various speeds. In addition, a DOF-based model of instantaneous human EE rate is employed to enable quantitative characterization of robotic walking EE relative to that of humans. The robot's instantaneous lower-body EE rates are consistent with its periodic walking cycle, and their relative trends between single and double support phases are analogous to those of humans. The robotic cost of transport (COT) curve as a function of normalized speed is also consistent with the human COT in terms of its convexity. Conversely, the contrasting distributions of EE throughout the robot and human DOFs and the robotic COT curve's considerably larger magnitudes, smaller speed ranges, and higher sensitivity to speed illustrate the energetic consequences of stable but inefficient static walking in the biped robot relative to the more efficient dynamic walking of humans. These energetic characteristics enable the identification of the joints and gait cycle phases associated with inefficiency in biped robotic gait, and reflect the noticeable differences in the system parameters (rigid and flat versus segmented feet) and gait control strategies (bent versus straight knees, instants of peak ankle actuator torques, static versus dynamic balance stability). The proposed general instrumentation provides a quantitative approach to benchmarking human gait as well as general guidelines for the development of energy-efficient walking robots.

This paper presents a formal framework for achieving multi-contact bipedal robotic walking, and realizes this methodology experimentally on two robotic platforms: AMBER2 and Assume The Robot Is A Sphere (ATRIAS). Inspired by the key feature encoded in human walking—multi-contact behavior—this approach begins with the analysis of human locomotion and uses it to motivate the construction of a hybrid system model representing a multi-contact robotic walking gait. Human-inspired outputs are extracted from reference locomotion data to characterize the human model or the spring-loaded invert pendulum (SLIP) model, and then employed to develop the human-inspired control and an optimization problem that yields stable multi-domain walking. Through a trajectory reconstruction strategy motivated by the process that generates the walking gait, the mathematical constructions are successfully translated to the two physical robots experimentally.

This paper first presents a method of motion planning and implementation for the self-recovery of an overturned six-legged robot. Previous studies aimed at the static and dynamic stabilization of robots for preventing them from overturning. However, no one can guarantee that an overturn accident will not occur during various applications of robots. Therefore, the problems involving overturning should be considered and solved during robot design and control. The design inspirations of multi-legged robots come from nature, especially insects and mammals. In addition, the self-recovery approach of an insect could also be imitated by robots. In this paper, such a self-recovery mechanism is reported. The inertial forces of the dangling legs are used to bias some legs to touch the ground, and the ground reaction forces exerted on the feet of landing legs are achieved to support and push the body to enable recovery without additional help. By employing the mechanism, a self-recovery approach named SSR (Sidewise-Self-Recovery) is presented and applied to multi-legged robots. Experiments of NOROS are performed to validate the effectiveness of the self-recovery motions. The results show that the SSR is a suitable method for multi-legged robots and that the hemisphere shell of robots can help them to perform self-recovery.

In this study, a bilateral teleoperation control algorithm is developed in which the model-mediation method is integrated with an impedance controller. The model-mediation method is also extended to three-degrees-of-freedom teleoperation. The aim of this controller is to compensate for instability issues and excessive forcing applied to the slave environment stemming from time delays in communication. The proposed control method is experimentally tested with two haptic desktop devices. Test results indicate that stability and passivity of the bilateral teleoperation system is preserved under variable time delays in communication. It is also observed that safer interactions of the slave system with its environment can be achieved by utilizing an extended version of the model-mediation method with an impedance controller.

There was an error in the spelling of the author's affiliation. Where the affiliation read “Department of mechanical engineering, Mashad Branch, Islamic Azad University, Mashad, Iran” it should instead have read “Department of mechanical engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran”.

The publisher regrets this error.

This paper introduces a solution to the problem of steering an aerodynamical system, with non-holonomic constraints superimposed on dynamic equations of motion. The proposed approach is a dimensionality reduction of the Optimal Control Problem (OCP) with heavy path constraints to be solved by Rapidly-Exploring Random Tree (RRT) algorithm. In this research, we formulated and solved the OCP with Euler–Lagrange formula in order to find the optimal-time trajectory. The RRT constructs a non-collision path in static, high-dense obstacle environment (i.e. heavy path constraint). Based on a real-world aircraft model, our simulation results found the collision-free path and gave improvements of time and fuel consumption of the optimized Hamiltonian-based model over the original non-optimized model.

This paper presents a novel motion planning approach inspired by the Dynamic Programming (DP) applicable to multi degree of freedom robots (mobile or stationary) and autonomous vehicles. The proposed discrete–time algorithm enables a robot to reach its destination through an arbitrary obstacle field in the fewest number of time steps possible while minimizing a secondary objective function. Furthermore, the resulting optimal trajectory is guaranteed to be globally optimal while incorporating state constraints such as velocity, acceleration, and jerk limits. The optimal trajectories furnished by the algorithm may be further updated in real time to accommodate changes in the obstacle field and/or cost function. The algorithm is proven to terminate in a finite number of steps without its computational complexity increasing with the type or number of obstacles. The effectiveness of the global and replanning algorithms are demonstrated on a planar mobile robot with three degrees of freedom subject to velocity and acceleration limits. The computational complexity of the two algorithms are also compared to that of an A*–type search.

As various robots are anticipated to coexist with humans in the near future, safe manipulation in unknown, cluttered environments becomes an important issue. Manipulation in an unknown environment, however, has been proven to be NP-Hard and the risk of unexpected human--robot collision hampers the dawning of the era of human--robot coexistence. We propose a non-contact-based sensitive skin as a means to provide safe manipulation hardware and interleaving planning between the workspace and the configuration space as software to solve manipulation problems in unknown, crowded environments. Novelty of the paper resides in demonstration of real time and yet complete path planning in an uncertain and crowded environment. To that end, we introduce the framework of the sensor-based interleaving planner (SBIP) whereby search completeness and safe manipulation are both guaranteed in cluttered environments. We study an interleaving mechanism between sensation in a workspace and execution in the corresponding configuration space for real-time planning in uncertain environments, thus the name interleaving planner implies.

Applications of the proposed system include manipulators of a humanoid robot, surgical manipulators, and robotic manipulators working in hazardous and uncertain environments such as underwater, unexplored planets, and unstructured indoor spaces.

This paper presents a novel forecasting kinematic algorithm for autonomously navigating the 3D visual window of laparoscopic minimally invasive surgical robotic system (LMISRS). By the application of the proposed technique, a constant distribution area ratio of the micro devices can be guaranteed in the visual window; real-time concurrency motion of the visual window of the laparoscope and the mark points of the instruments is realized, i.e. the visual window can keep tracking the movement of the marks automatically, so that the user does not have to switch between the master-slave controlling targets. The implementation of the new technique is summarized as follows: the robotic kinematics and space analytic geometry are thoroughly analyzed and modeled, and a “following kinematic algorithm” is proposed for the visual window of the laparoscope, which tracks the mark points of the instrument arms; a “forecasting kinematic algorithm” is established by using a combination of the “following kinematic algorithm”, the basic visual parameters of 3D visual field, the Verhulst Grey Model and the filtered amendment method. The proposed technique is verified by a series of simulations by using two groups of marks' motion trails with different sampling times, indicating that the technique is accurate, feasible and robust.