In this paper, a new biomimetic tendon-driven actuation system for prosthetic and wearable robotic hand applications is presented. It is based on the combination of compliant tendon cables and one-way shape memory alloy (SMA) wires that form a set of agonist–antagonist artificial muscle pairs for the required flexion/extension or abduction/adduction of the finger joints. The performance of the proposed actuation system is demonstrated using a 4 degree-of-freedom (three active and one passive) artificial finger testbed, also developed based on a biomimetic design approach. A microcontroller-based pulse-width-modulated proportional-derivation (PWM-PD) feedback controller and a minimum jerk trajectory feedforward controller are implemented and tested in an ad hoc fashion to evaluate the performance of the finger system in emulating natural joint motions. Part II describes the dynamic modeling of the above nonlinear system, and the model-based controller design.

This paper presents the simplest walking model with an upper body. The model is a passive dynamic walker, i.e. it walks down a slope without motor input or control. The upper body is confined to the midway angle of the two legs. With this kinematic constraint, the model has only two degrees of freedom. The model achieves surprisingly successful walking results: it can handle disturbances of 8% of the initial conditions and it has a specific resistance of only 0.0725(−).

A novel affect-sensitive human-robot cooperative framework is presented in this paper. Peripheral physiological indices are measured through wearable biofeedback sensors to detect the affective state of the human. Affect recognition is performed through both quantitative and qualitative analyses. A subsumption control architecture sensitive to the affective state of the human is proposed for a mobile robot. Human-robot cooperation experiments are performed where the robot senses the affective state of the human and responds appropriately. The results presented here validate the proposed framework and demonstrate a new way of achieving implicit communication between a human and a robot.

In this paper we propose some simple rules for PID tuning of robot manipulators. The procedure suggested requires the knowledge of the structure of the inertia matrix and the gravitational torque vector of the robot dynamics, but only upper bounds on the dynamics parameters are needed. This tuning procedure is extracted from the stability analysis by using a suitable Lyapunov function together with the LaSalle invariance principle. We show that with this guideline, the overall closed-loop system is asymptotically stable. This procedure is illustrated for a two degrees-of-freedom robot

We address the synthesis of controllers for a swarm of robots to generate a desired two-dimensional geometric pattern specified by a simple closed planar curve with local interactions for avoiding collisions or maintaining specified relative distance constraints. The controllers are decentralized in the sense that the robots do not need to exchange or know each other's state information. Instead, we assume that the robots have sensors allowing them to obtain information about relative positions of neighbors within a known range. We establish stability and convergence properties of the controllers for a certain class of simple closed curves. We illustrate our approach through simulations and consider extensions to more general planar curves.

Often inspection and maintenance work involve a large number of highly dangerous manual operations, especially within industrial fields such as shipbuilding and construction. This paper deals with the autonomous climbing robot which uses the “caterpillar” concept to climb in complex 3D metallic-based structures. During its motion the robot generates in real-time the path and grasp planning in order to ensure stable self-support to avoid the environment obstacles, and to optimise the robot consumption during the inspection. The control and monitoring of the robot is achieved through an advanced Graphical User Interface to allow an effective and user friendly operation of the robot. The experiments confirm its advantages in executing the inspection operations.

This paper presents the software package SYMORO+ for the automatic symbolic modelling of robots. This package permits to generate the direct geometric model, the inverse geometric model, the direct kinematic model, the inverse kinematic model, the dynamic model, and the inertial parameters identification models.

The structure of the robots can be serial, tree structure or containing closed loops. The package runs on Sun stations and PC computers, it has been developed under MATHEMATICA and C language. In this paper we give an overview of the algorithms used in the different models; the computational cost of the dynamic models of the PUMA robot are given.

Algebraic methods in connection with classical multidimensional geometry have proven to be very efficient in the computation of direct and inverse kinematics of mechanisms as well as the explanation of strange, pathological behavior. In this paper, we give an overview of the results achieved within the last few years using the algebraic geometric method, geometric preprocessing, and numerical analysis. We provide the mathematical and geometrical background, like Study's parametrization of the Euclidean motion group, the ideals belonging to mechanism constraints, and methods to solve polynomial equations. The methods are explained with different examples from mechanism analysis and synthesis.

The absolute accuracy of a small industrial robot is improved using a 30-parameter calibration model. The error model takes into account a full kinematic calibration and five compliance parameters related to the stiffness in joints 2, 3, 4, 5, and 6. The linearization of the Jacobian is performed to iteratively find the modeled error parameters. Two coordinate measurement systems are used independently: a laser tracker and an optical CMM. An optimized end-effector is developed specifically for each measurement system. The robot is calibrated using fewer than 50 configurations and the calibration efficiency validated in 1000 configurations using either the laser tracker or the optical CMM. A telescopic ballbar is also used for validation. The results show that the optical CMM yields slightly better results, even when used with the simple triangular plate end-effector that was developed mainly for the laser tracker.

Robots are expected to be pervasive in the society in a not too distant future where they will work extensively as assistants of humans in various activities. With this in view, a novel affect-sensitive architecture for human-robot cooperation is presented in this paper where the robot is expected to recognize human psychological states. As a demonstration, an online heart rate variability analysis to infer the mental stress of a human engaged in a task is presented. This technique involves real-time heart rate monitoring, signal processing using both Fourier Transforrn and Wavelet Transform, and inferring the stress condition based on the level of activation of the sympathetic and parasympathetic nervous systems using fuzzy logic. Results from human subject trials are presented to validate the presented methodology. This stress detection technique is expected to be useful in the future human-robot cooperation activities, where the robot will recognize human stress and respond appropriately.

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.

Inaccurate positioning of the robot end effector causes joint deformation as well as geometric errors when an industrial robot has a payload at its end effector. We propose a new approach of calibration which deals with joint angle dependent errors to compensate for these phenomena. To implement this method, we divided the robot workspace into several local regions, and built a calibration equation by generating the constraint conditions of the end effector's motion in each local region using a three-dimensional position measurement system. The parameter errors obtained this way were interpolated using the Radial Basis Function Network (RBFN) so as to estimate calibration errors in the regions that we did not measure. We used this technique to improve the performance of a six DOF industrial robot used for arc welding.

There have been significant interests and efforts in the field of impedance control on robotic manipulation over last decades. Impedance control aims to achieve the desired mechanical interaction between the robotic equipment and its environment. This paper gives the overview and comparison of basic concepts and principles, implementation strategies, crucial techniques, and practical applications concerning the impedance control of robotic manipulation. This work attempts to serve as a tutorial to people outside the field and to promote discussion of a unified vision of impedance control within the field of robotic manipulation. The goal is to help readers quickly get into the problems of their interests related to impedance control of robotic manipulation and to provide guidance and insights in finding appropriate strategies and solutions.

This article deals with the kinematic calibration of the Delta robot. Two different calibration models are introduced: The first one takes into account deviations of all mechanical parts except the spherical joints, which are assumed to be perfect (“model 54”), the second model considers only deviations which affect the position of the end-effector, but not its orientation, assuming that the “spatial parallelogram” remains perfect (“model 24”). A measurement set-up is presented which allows to determine the end-effector's position and orientation with respect to the base. The measurement points are later be used to identify the parameters of the two calibration model resulting in an accuracy improvement of a factor of 12.3 for the position and a factor of 3.7 for the prediction of the orientation.

This paper analyzes the dynamics and control of pinch motions generated by a pair of two multi-degrees-of-freedom robot fingers with soft and deformable tips pinching a rigid object. It is shown firstly that passivity analysis leads to an effective design of a feedback control signal that realizes dynamic stable pinching (grasping), even if extra terms of Lagrange's multipliers arise from holonomic constraints of tight area-contacts between soft finger-tips and surfaces of the rigid object and exert torques and forces on the dynamics. It is shown secondly that a principle of superposition is applicable to the design of additional feedback signals for controlling both the posture (rotational angle) and position (some of task coordinates of the mass center) of the object provided that the number of degrees of freedom of each finger is specified for satisfying a condition of stationary resolution of controlled position state variables. The details of feedback signals are presented in the case of a special setup consisting of two robot fingers with two degrees of freedom.

In this paper, a new application of the ZMP (Zero Moment Point) control law is presented. The objective of this control method is to obtain a smooth and soft motion based on a real-time control. In the controller, the ZMP is treated as an actuating signal. The coordinates of the robot body are fed back to obtain its position. The proposed control method was applied on two different biped robots, and its validity is verified experimentally.

The problem of determining energy optimal walking motions for a bipedal walking robot is considered. A full dynamic model of a planar seven-link biped with feet is derived including the effects of impact of the feet with the ground. Motions of the hip and feet during a regular step are then modelled by 3rd order polynomials, the coefficients of which are obtained by numerically minimising an energy cost function. Results are given in the form of walking profiles and energy curves for the specific cases of motion over level ground, motion up and down an incline, and varying payload.

A system including Global Positioning Systems (GPS) and digital cartography is a good solution to carry out vehicle's guidance. However, it has inconveniences like high sensibility to multipath and interference when the GPS signal is blocked by external agents. Another system is mandatory to avoid this error. This paper presents a cooperative system based on GPS and Inertial Navigation Systems (INS) for automated vehicle position. The control system includes a decision unit to choose which value is the correct. In case GPS is working at top precision, it takes the control. On the other part, GPS signal can be lost and inertial control system guides the car in this occasion. A third possibility is contemplated: we receive the signal from GPS but the accuracy is over one meter. Now, position value is obtained by means of both systems. Experimental results analyze two situations: guidance in an urban area where GPS signal can be occluded by buildings or trees during short time intervals and the possibility of loss of the signal in long time to simulate the circulation in tunnels. Good results have been observed in tests and it demonstrates how a cooperative system improves the automated vehicle guidance.

This paper presents an investigation of odor localization by groups of autonomous mobile robots using principles of Swarm Intelligence. First, we describe a distributed algorithm by which groups of agents can solve the full odor localization task more efficiently than a single agent. Next, we demonstrate that a group of real robots under fully distributed control can successfully traverse a real odor plume, and that an embodied simulator can faithfully reproduce these real robots experiments. Finally, we use the embodied simulator combined with a reinforcement learning algorithm to optimize performance across group size, showing that it can be useful not only for improving real world odor localization, but also for quantitatively characterizing the influence of group size on task performance.

A small-scale flexure-based gripper was designed for manipulation tasks requiring precision position and force control. The gripper is actuated by a piezoelectric ceramic stack actuator and utilizes strain gages to measure both the gripping force and displacement. The position and force bandwidths were designed for ten Hertz and one hundred Hertz, respectively, in order to afford human-based teleoperative transparency. The gripper serves effectively as a one degree-of-freedom investigation of compliant mechanism design for position and force controlled micromanipulation. Data is presented that characterizes the microgripper performance under both pure position and pure force control, followed by a discussion of the attributes and limitations of flexure-based design.