In this paper, a pseudoinverse-type bi-criteria minimization scheme is proposed and investigated for the redundancy resolution of robot manipulators at the joint-acceleration level. Such a bi-criteria minimization scheme combines the weighted minimum acceleration norm solution and the minimum velocity norm solution via a weighting factor. The resultant bi-criteria minimization scheme, formulated as the pseudoinverse-type solution, not only avoids the high joint-velocity and joint-acceleration phenomena but also causes the joint velocity to be near zero at the end of motion. Computer simulation results based on a 4-Degree-of-Freedom planar robot manipulator comprising revolute joints further verify the efficacy and flexibility of the proposed bi-criteria minimization scheme on robotic redundancy resolution.

In this paper a complete and systematic procedure for the identification of the dynamic parameters of rigid robot manipulators is presented. Starting from the basic results on the subject present in the literature and on a new technique to find exciting trajectories for the estimation, the procedure is developed. A set of algorithms is provided for the implementation of the various steps of the procedure for a generic open-chain structure. The algorithms have been coded in the popular Matlab/Maple environment and the procedure has been tested in a practical case study to identify the dynamic parameters of a six-degree-of-freedom conventional industrial robot.

Mobile olfactory robots can be used in a number of relevant application areas where a better understanding of a gas distribution is needed, such as environmental monitoring and safety and security related fields. In this paper, we present a method to integrate the classification of odours together with gas distribution mapping. The resulting odour map is then correlated with the spatial information collected from a laser range scanner to form a combined map. Experiments are performed using a mobile robot in large and unmodified indoor and outdoor environments. Multiple odour sources are used and are identified using only transient information from the gas sensor response. The resulting multi-level map can be used as a representation of the collected odour data.

This paper investigates the neural network approach to solve the inverse kinematics problem of redundant robot manipulators in an environment with obstacles. The solution technique proposed requires only the knowledge of the robot forward kinematics functions and the neural network is trained in the inverse modeling manner. Training algorithms for both the obstacle free case and the obstacle avoidance case are developed. For the obstacle free case, sample points can be selected in the work space as training patterns for the neural network. For the obstacle avoidance case, the training algorithm is augmented with a distance penalty function. A ball-covering object modeling technique is employed to calculate the distances between the robot links and the objects in the work space. It is shown that this technique is very computationally efficient. Extensive simulation results are presented to illustrate the success of the proposed solution schemes. Experimental results performed on a PUMA 560 robot manipulator is also presented.

The paper introduces a family of three-DOFs translational-rotational Parallel-Kinematics Mechanisms (PKMs) as well as the mobility analysis of such family using Lie-group theory. Each member of this family has two-rotational one-translational DOFs. A novel mechanism is presented and analyzed as a representative of that family. The use and the practical value of that modular mechanism are emphasized.

In this paper, the inverse dynamics of the 6-dof out-parallel manipulator is formulated by means of the principle of virtual work and the concept of link Jacobian matrices. The dynamical equations of motion include the rotation inertia of motor–coupler–screw and the term caused by the external force and moment exerted at the moving platform. The approach described here leads to efficient algorithms since the constraint forces and moments of the robot system have been eliminated from the equations of motion and there is no differential equation for the whole procedure. Numerical simulation for the inverse dynamics of a 6-dof out-parallel manipulator is illustrated. The whole actuating torques and the torques caused by gravity, velocity, acceleration, moving platform, strut, carriage, and the rotation inertia of the lead screw, motor rotor and coupler have been computed.

The current designs of commercial artificial hands have a low level of innovation. As feedback to the user is difficult to achieve reliably, most devices are simple in design and operation, and limited in functional range. If information on the state of the hand, the forces and any slippage that is occurring is fed back to a microcontroller then more than one degree of freedom can be controlled and a greater and more natural functional range is possible. This paper describes the development of such a device. It outlines the design requirements, the methods of detection of the signals and the training required to operate the hand.

Tendon sheath actuation is found in many applications, particularly in robotic hands and surgical robots. Due to the friction between the tendon and sheath, many undesirable characteristic such as backlash, hysteresis and non-linearity are present. It is desirable to know the end-effector force and elongation of the tendon to control the system effectively, but it is not always feasible to fix sensors at the end effector. A method to estimate the end-effector parameters using only a force and position sensor at the proximal site is given. An analytical study is presented and experiments are reported to support the result, showing a maximum full-scale error of approximately 7%. This result is achieved if the shape of the sheath remains the same and buckling is negligible. The results presented in this study could contribute towards haptic development in robotics surgery.

The aerial manipulator is a special and new type of flying robot composed of a rotorcraft unmanned aerial vehicle (UAV) and a/several manipulator/s. It has gained a lot of attention since its initial appearance in 2010. This is mainly because it enables traditional UAVs to conduct versatile manipulating tasks from air, considerably enriching their applications. In this survey, a complete and systematic review of related research on this topic is conducted. First, various types of structure designs of aerial manipulators are listed out. Subsequently, the modeling and control methods are introduced in detail from the perspective of two types of typical application cases: free-flight and motion-restricted operations. Finally, challenges for future research are presented.

We determine the shortest (minimal in length) path on a unicycle-like mobile robot in a known environment with smooth (possibly non-convex) obstacles with a constraint on curvature of their boundaries. Furthermore, we propose a new reactive randomized algorithm of robot navigation in unknown environment and prove that the robot will avoid collisions and reach a steady target with probability 1. The performance of our algorithm is confirmed by computer simulations and outdoor experiments with a Pioneer P3-DX mobile wheeled robot.

The problem studied in this paper is a mobile robot that autonomously navigates in a domestic environment, builds a map as it moves along and localizes its position in it. In addition, the robot detects predefined objects, estimates their position in the environment and integrates this with the localization module to automatically put the objects in the generated map. Thus, we demonstrate one of the possible strategies for the integration of spatial and semantic knowledge in a service robot scenario where a simultaneous localization and mapping (SLAM) and object detection recognition system work in synergy to provide a richer representation of the environment than it would be possible with either of the methods alone. Most SLAM systems build maps that are only used for localizing the robot. Such maps are typically based on grids or different types of features such as point and lines. The novelty is the augmentation of this process with an object-recognition system that detects objects in the environment and puts them in the map generated by the SLAM system. The metric map is also split into topological entities corresponding to rooms. In this way, the user can command the robot to retrieve a certain object from a certain room. We present the results of map building and an extensive evaluation of the object detection algorithm performed in an indoor setting.

Miniaturized surgical devices are promising for the future development of minimally invasive and endoluminal surgery. However, the dexterity and therapeutic functions of these devices are limited. In this paper, a reconfigurable modular robotic system is proposed to perform screening and interventions in the gastrointestinal tract. In the proposed system, millimeter-sized robotic modules are ingested and tasked to assemble into an articulated mechanism in the stomach cavity. The modules are assembled according to the target location to perform precise intervention. Based on this concept, a preliminary report is presented covering the robotic schemes for the endoluminal reconfigurable platform, the design with structural functions, the control strategy, and the interval-based constraint satisfaction algorithm to determine the suitable topologies of the reconfigurable robot for the given task.

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.

A humanoid robot should be able to keep balance even in the presence of disturbing forces. Studies of human body reaction patterns to sudden external forces (impacts) are useful for developing balance control strategies. In this paper, we show how to implement two such reaction patterns, called ankle and hip strategy, using a small humanoid robot. Simple dynamical models in the sagittal plane are employed. The decision for invoking one of the reaction patterns is based on acceleration data measured during the impact. The experiments confirm that the robot is able to react swiftly, similar to a human.

The experimental evidence supports the validity of the principle of superposition for multi-finger prehension in humans. Forces and moments of individual digits are defined by two independent commands: “Grasp the object stronger/weaker to prevent slipping” and “Maintain the rotational equilibrium of the object”. The effects of the two commands are summed up.

This paper presents a simple numerical method for forward kinematics of general Stewart–Gough platforms, which can generate a unique solution directly. This method utilizes the trivial nature of the inverse kinematics of parallel manipulators, and derives a straightforward linear relationship between the small change in joint variables (leg lengths) and the resulting small motion of the platform. The solution to the forward kinematics is then achieved through a series of small changes in joint variables. Numerical examples validate and confirm the efficiency of the method.

Autonomous walking bipedal machines, possibly useful for rehabilitation and entertainment purposes, need a high energy efficiency, offered by the concept of ‘Passive Dynamic Walking' (exploitation of the natural dynamics of the robot). 2D passive dynamic bipeds have been shown to be inherently stable, but in the third dimension two problematic degrees of freedom are introduced: yaw and roll.

We propose a design for a 3D biped with a pelvic body as a passive dynamic compensator, which will compensate for the undesired yaw and roll motion, and allow the rest of the robot to move as if it were a 2D machine. To test our design, we perform numerical simulations on a multibody model of the robot. With limit cycle analysis we calculate the stability of the robot when walking at its natural speed.

The simulation shows that the compensator, indeed, effectively compensates for both the yaw and the roll motion, and that the walker is stable.

This survey paper is focused on the navigation of mobile robots. The most important associated problems and the solutions given by different researchers are discussed. Several aspects are not yet satisfactorily resolved and some promising research approaches are addressed.

We present simulated monopedal and bipedal robots that are capable of open-loop stable periodic running motions without any feedback even though they have no statically stable standing positions. Running as opposed to walking involves flight phases which makes stability a particularly difficult issue. The concept of open-loop stability implies that the actuators receive purely periodic torque or force inputs that are never altered by any feedback in order to prevent the robot from falling. The design of these robots and the choice of model parameter values leading to stable motions is a difficult task that has been accomplished using newly developed stability optimization methods.

This paper addresses the link position setpoint control problem of n–link robotic manipulators with amplitude-limited control inputs. We design a global-asymptotic exact model knowledge controller and a semi-global asymptotic controller which adapts for parametric uncertainty. Explicit bounds for these controllers can be determined; hence, the required input torque can be calculated a priori so that actuator saturation can be avoided. We also illustrate how the proposed control algorithm in this paper can be slightly modified to produce a proportional-integral-derivative (PID) controller which contains a saturated integral term. Experimental results are provided to illustrate the improved performance of the proposed control strategy over a standard adaptive controller that has been artificially limited to account for torque saturation.