In this paper the design and operation for a 2-Degree-of-Freedom, leg–wheel hybrid mobile robot are presented. A prototype of a low-cost and easy-to-use system, which is capable of straight walking and steering with two actuators only, has been designed and built. Simulation and experimental tests have been carried out to verify the engineering feasibility and operation of the proposed solution. The designed robot can be used for applications such as surveillance and inspection of disaster sites.

This paper shows that a well-known causal PD controller plus feedforward solves the global output feedback tracking control problem of robot manipulators, by requiring only the existence of the robot natural damping, no matter how small. To this end, we first demonstrate that a robot controlled by a causal PD is globally input-to-state stable (ISS) with respect to a bounded input disturbance. Then, we prove that the addition of a feedforward compensation renders the error system uniformly globally asymptotically stable. Furthermore, we present a possible extension to more general nonlinear systems and also to uncertain systems.

A practical architecture, using a four-bar-linkage, is considered for the University of Minnesota direct drive rotot. This statically-balanced direct drive robot has been constructed for stability analysis of the robot in constrained maneuvers.2–6 As a result of the elimination of the gravity forces (without any counter weights), smaller actuators and consequently smaller amplifiers were chosen. The motors yield acceleration of 5 g at the robot end point without overheating. High torque, low speed, brush-less AC synchronous motors are used to power the robot. Graphite-epoxy composite material is used for the construction of the robot links. A 4-node parallel processor has been used to control the robot. The dynamic tracking accuracy-with the feedforward torque method as a control law- has been derived experimentally.

Many industrial robots employ closed-loop actuating elements such as the parallelogram mechanism for increased stiffness. Modeling these manipulators for the purpose of calibration presents a challenge due to complex nonlinear couplings between parameters of the chains. The modeling method presented in this paper involves the integration of the open- and closed-loop elements whose errors can be resolved as linear functions of their parameters. As a result, the model is similar to that of a serial-link robot, which makes it possible to use existing well-defined calibration techniques in the area. Simulation and experimental studies on an industrial robot for verifying the correctness and effectiveness of the proposed model are also described.

Wire-actuated parallel manipulators and their failures are studied in this paper taking into consideration their failure modes. A methodology for investigating the effect of wire/actuator failures on the force/moment capability of manipulators is presented, and the criteria for full and partial recovery from these failures are established. The methodology is also applicable for the cases that the minimum norm solution for the vector of wire tensions gives a negative value for tension by treating the corresponding wire as failed. The proposed criteria are also valid for the manipulators that utilize hybrid actuation of wires and joints. Three planar wire-actuated parallel manipulators are used as the case study to illustrate the proposed methodology and criteria.

Surgical robotics is a growing discipline, continuously expanding with an influx of new ideas and research. However, it is important that the development of new devices take account of past mistakes and successes. A structured approach is necessary, as with proliferation of such research, there is a danger that these lessons will be obscured, resulting in the repetition of mistakes and wasted effort and energy. There are several research paths for surgical robotics, each with different risks and opportunities and different methodologies to reach a profitable outcome. The main emphasis of this paper is on a methodology for ‘applied research’ in surgical robotics. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers, the most important first two tiers, and thus gain some acceptability. However, the lack of conformity to the criteria in the top tier, and the inability to conclusively prove increased clinical benefit, is shown to be hampering their potential in gaining wide establishment.

In this paper, a rigid–flexible planar parallel manipulator (PPM) actuated by three linear ultrasonic motors for high-accuracy positioning is proposed. Based on the extended Hamilton's principle, a rigid–flexible dynamic model of the proposed PPM is developed utilizing exact boundary conditions. To derive an appropriate low-order dynamic model for the design of the controller, the assumed modes method is employed to discretize elastic motion. Then to investigate the interaction between the rigid and elastic motions, a proportional derivative feedback controller combined with a feed-forward-computed torque controller is developed to achieve motion tracking while attenuating the residual vibration. Then the controller is extended to incorporate an input shaper for the further suppression of residual vibration of flexible linkages. Computer simulations are presented as well as experimental results to verify the proposed dynamic model and controller. The input shaping method is verified to be effective in attenuating residual vibration in a highly coupled rigid–flexible PPM. The procedure employed for dynamic modeling and control analysis provides a valuable contribution into the vibration suppression of such a PPM.

Mobile robots are used to operate in urban environments, for surveillance, reconnaissance, and inspection, as well as for military operations and in hazardous environments. Some are intended for exploration of only natural terrains, but others also for artificial environments, including stairways. This paper presents a mobile robot design that achieves autonomous climbing and descending of stairs. The robot uses sensors and embedded intelligence to achieve the task. The robot is a reconfigurable tracked mobile robot that has the ability to traverse obstacles by changing its track configuration. Algorithms have been further developed for conditions under which the mobile robot would halt its motion during the climbing process when at risk of flipping over. Technical problems related to the implementation of some of the robot functional attributes are presented, and proposed solutions are validated and experimentally tested. The experiments illustrate the effectiveness of the proposed approach to autonomous climbing and descending of stairs.

This paper proposes an alternative environment mapping method for accurate robotic navigation based on 3D information. Typical techniques for 3D mapping using occupancy grid require intensive computational workloads in order to both build and store the map. This work introduces an Occupancy-Elevation Grid (OEG) mapping technique, which is a discrete mapping approach where each cell represents the occupancy probability, the height of the terrain and its variance. This representation allows a mobile robot to know with an accurate degree of certainty whether a place in the environment is occupied by an obstacle and the height of such obstacle. Thus, based on its hardware characteristics, it can make calculations to decide if it is possible to traverse that specific place. In general, the map representation introduced can be used in conjunction with any kind of distance sensor. In this work, we use laser range data and stereo system data with a probabilistic treatment. The resulting maps allow the execution of tasks as decision making for autonomous navigation, exploration, localization and path planning, considering the existence and the height of the obstacles. Experiments carried out with real data demonstrate that the proposed approach yields useful maps for autonomous navigation.

Topics relevant to modeling and control of mobile wheeled robots with a differential drive are discussed by assuming a motion that is planar and free from lateral and longitudinal slippages, and by taking into account dynamic and kinematic properties of the vehicle. Based on the concept of geometric path-tracking, a controller is designed that is a memoryless function of the lateral, heading, and velocity path-tracking offsets. If these offsets are kept small and the assigned tracking velocity is constant, then this controller may be given a linear, time-invariant and decoupled PID (Proportional + integral + derivative) structure.

This paper presents a novel method for localization of mobile robots in structured environments. The estimation of the position and orientation of the robot relies on the minimisation of the partial Hausdorff distance between ladar range measurements and a floor plan image of the building. The approach is employed in combination with an extended Kalman filter to obtain accurate estimates of the robot's position, heading and velocity. Good estimates of these variables were obtained during tests performed using a differential drive robot, thus demonstrating that the approach provides an accurate, reliable and computationally feasible alternative for indoor robot localization and autonomous navigation.

When generating gaits for soft robots (those with no explicit joints), it is not evident that undulating control schemes are the most efficient. In considering alternative control schemes, however, the computational costs of evaluating continuum mechanic models of soft robots represent a significant bottleneck. We consider the use of lumped dynamic models for soft robotic systems. Such models have not been employed previously to design gaits for soft robotic systems, though they are widely used to simulate robots with compliant joints. A major question is whether these methods are accurate enough to be representations of soft robots to enable gait design and optimization. This paper addresses the potential “reality gap” between simulation and experiment for the particular case of a soft caterpillar-like robot. Experiments with a prototype soft crawler demonstrate that the lumped dynamic model can capture essential soft-robot mechanics well enough to enable gait optimization. Significantly, experiments verified that a prototype robot achieved high performance for control patterns optimized in simulation and dramatically reduced performance for gait parameters perturbed from their optimized values.

A brief history of robotic surgery is provided, which describes the transition from autonomous robots to hands-on systems that are under the direct control of the surgeon. An example of the latter is the Acrobot (for active-constraint robot) system used in orthopaedics, whilst soft-tissue surgery is illustrated by the daVinci telemanipulator system. Non-technological aspects of robotic surgery have often been a major impediment to their widespread clinical use. These are discussed in detail, together with the role of navigation systems, which are considered a major competitor to surgical robots. A detailed description is then given of a registration method for robots to achieve improved accuracy. Registration is a major source of error in robotic surgery, particularly in orthopaedics. The paper describes the design and clinical implementation of a novel method, coined the bounded registration method, applied to minimally invasive registration of the femur. Results of simulations which compare the performance of bounded registration with a standard implementation of the iterative closest point algorithm are also presented, alongside a description of their application in the Acrobot hands-on robot, used clinically for uni-condylar knee arthroplasty.

Modeling the instantaneous kinematics of lower pair linkages using joint screws and the finite kinematics with Lie group concepts is well established on a solid theoretical foundation. This allows for modeling the forward kinematics of mechanisms as well the loop closure constraints of kinematic loops. Yet there is no established approach to the modeling of complex mechanisms possessing multiple kinematic loops. For such mechanisms, it is crucial to incorporate the kinematic topology within the modeling in a consistent and systematic way. To this end, in this paper a kinematic model graph is introduced that gives rise to an ordering of the joints within a mechanism and thus allows to systematically apply established kinematics formulations. It naturally gives rise to topologically independent loops and thus to loop closure constraints. Geometric constraints as well as velocity and acceleration constraints are formulated in terms of joint screws. An extension to higher order loop constraints is presented. It is briefly discussed how the topology representation can be used to amend structural mobility criteria.

A general methodology and associated computational algorithm for predicting postures of the digital human upper body is presented. The basic plot for this effort is an optimization-based approach, where we believe that different human performance measures govern different tasks. The underlying problem is characterized by the calculation (or prediction) of the human performance measure in such a way as to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized, subject to a number of constraints, including joint limits. The formulation is demonstrated and validated. We present this computational formulation as a broadly applicable algorithm for predicting postures using one or more human performance measures.

The Ankle Mimicking Prosthetic (AMP-) Foot 2 is a new energy efficient, powered transtibial prosthesis mimicking intact ankle behavior. The author's research is focused on the use of a low power actuator which stores energy in springs during the complete stance phase. At push-off, this energy can be released hereby providing propulsion forces and torques to the amputee. With the use of the so-called catapult actuator, the size and weight of the drive can be decreased compared to state-of-the-art powered prostheses, while still providing the full power necessary for walking.

In this article, the authors present a detailed description of the catapult actuator followed by a comparison with existing actuator technology in powered prosthetic feet with regard to torque and power requirements. The implication on the actuator's design will then be outlined. Further, a description of the control strategy behind the AMP-Foot 2 and 2.1 will be given. In the last section of the article, the actuation principle and control are illustrated by experimental validation with a transfemoral amputee. Conclusions and future work complete the paper.

In this paper, a novel spherical parallel manipulator and its isotropic design is introduced. This manipulator has good accuracy and relatively a larger workspace which is free of singularities. Utilizing spherical configuration the forward position problem is solved by equivalent angle–axis representation and Bezout's method which leads to a polynomial of degree 8. Two examples are given, one for isotropic and one for nonisotrpoic design. The first case results in eight real solutions, therefore, the polynomial being minimal. Using invariant form, we study acceleration analysis, conditions for singularity and find infinite isotropic structures. Accuracy and workspace analysis are also performed and are shown to have good global conditioning index and relatively large workspace. Using isotropic design and singularity requirements, we show the workspace of isotropic design is free of singularity.

An unmanned aerial vehicle (UAV) dynamic path planning method is proposed to avoid not only static threats but also mobile threats. The path of a UAV is planned or modified by the potential trajectory of the mobile threat, which is predicted by its current position, velocity, and direction angle, because the positions of the UAV and mobile threat are dynamically changing. In each UAV planning path, the UAV incurs some costs, including control costs to change the direction angle, route costs to bypass the threats, and threat costs to acquire some probability to be destroyed by threats. The model predictive control (MPC) algorithm is used to determine the optimal or sub-optimal path with minimum overall costs. The MPC algorithm is a rolling-optimization feedback algorithm. It is used to plan the UAV path in several steps online instead of one-time offline to avoid sudden and mobile threats dynamically. Lastly, solution implementation is described along with several simulation results that demonstrate the effectiveness of the proposed method.

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.

Verbal communication is the most natural way of human–robot interaction. Such an interaction is usually achieved by means of a human-robot interface (HRI). In this paper, a HRI is presented to teleoperate a robotic platform via the user's voice. Hence, a speech recognition system is necessary. In this work, a user-dependent acoustic model for Spanish speakers has been developed to teleoperate a robot with a set of commands. Experimental results have been successful, both in terms of a high recognition rate and the navigation of the robot under the control of the user's voice.