IROS 2015 论文列表

This paper presents a control method of multi-DOF power assistant robots for anatomical multi-axis joints such as the wrist and the ankle. It is difficult to calculate the accurate direction of human motion intention during manipulating an object due to discrepancy between the calculated force from F/T sensor and the real human intention. Only using an sEMG is not an adequate method of power assistance for unknown external perturbation in the anatomical multi-axis joint, because the sEMG signal cannot figure out where the intention vector exists during interactions. This paper proposes a robust control method of power-assistant robots for unknown external perturbation during manipulating an object by using both the F/T sensor and sEMG. The specific purpose of this study to control the exoskeleton robot for the wrist motion during manipulating an object, although the accurate intention vector of the wrist joint is unknown. It was verified that the proposed method generates the assisted power to follow the human motion intention even in the case of unknown external forces through experiments.

Lack of dexterous control over the position of a catheter's distal tip and not having any feedback from the quality of tip - tissue contact are among the factors that make the conventional catheter-based method of performing cardiac ablation very challenging. To resolve these issues, in this paper, we present a robotic catheter manipulation system that accommodates a conventional ablation catheter, places the ablation tip at the desired target and reports the forces that the tip exerts on the environment in real-time. In this system, the manual proximal handle is replaced with a mechanism that is capable of measuring the tension force along the pull-wire while actuating it to flex the distal shaft of the catheter. The placement of force/pressure sensors at the distal end of the catheter is avoided by developing a model-based force estimation technique using the measured tension force and information on the position and orientation of the distal tip. The developed system is further enhanced with an interface to assist the user in placing the catheter tip at the desired location while providing him/her with a real-time measure of the contact force. Extensive experiments show that using the proposed robotic system, the catheter tip is positioned within ±1 mm of the designated target and contact forces are reported in real-time with an accuracy of 3 gf.

A system for actively changing the stiffness of a long, thin, flexible robotic manipulator has been designed for cardiologists to use in a range of diagnosis and treatment procedures. Low-stiffness manipulators, such as catheters, are ideal for steering through vasculature with low risk of tissue injury. However, such instruments are not well-suited for applying force to tissue. The proposed system solves this problem by using a series of bead-shaped vertebrae containing pull wires to actively change the stiffness of the catheter, similar to gooseneck surgical retractors. Individual wires steer the catheter to a desired location. All wires are then tensioned to create friction between each vertebra and prevent sliding, therefore resisting motion. While this design concept has been implemented manually in various settings for decades, fine robotic control of the friction and stiffness of the system relies on a thorough understanding of the friction properties between vertebral segments. We have developed an analytical model to understand the interactions between vertebrae and determine the relationships between system parameters and the overall stiffness of the catheter. Experiments validated the calculations from the model and the functionality of the system by applying known loads to the tip of the catheter and measuring the catheter displacement. The catheter stiffness was measured to range from 100 N/m to 800 N/m, which is sufficient for performing many surgical tasks on tissue. This system can be useful in minimally invasive procedures involving direct instrument contact with tissue by improving accuracy, safety, and work flow.

A robot localization system is presented that enables a robot to estimate its position within some space by passively receiving ultra-wideband radio signals from fixed-position modules. Communication from the fixed-position modules is one-way, allowing the system to scale to multiple robots. Furthermore, the system's high position update rate makes it suitable to be used in a feedback control system, and enables the robot to track and perform high-speed, dynamic motions. This paper describes the algorithmic underpinnings of the system, discusses design decisions and their impact on the performance of the resulting localization, and highlights challenges faced during implementation. Performance of the localization system is experimentally verified through comparison with data from a motion-capture system. Finally, the system's application to robot self-localization is demonstrated through integration with a quadrocopter.

The integration of eye-gaze tracking at the console of surgical robots has the potential to add both speed and functionality to the human-robot interface. In this paper, we present a novel eye gaze tracker that can be integrated as a simple retrofit to the da Vinci console. In particular, the eye tracker can be used with the da Vinci Research Kit (dVRK) to control the patient side manipulators. We present the eye-tracker design and calibration. First, a 2D calibration is carried out to estimate the gaze on the da Vinci's stereoscopic display, followed by a 3D “hand-eye” calibration to estimate the gaze in the surgical scene. Using the dVRK, we demonstrated the use of the eye-tracker to perform a gaze-assisted task, in which the estimated gaze is used as a set point for the robot and the user is guided towards the point of gaze through haptic feedback. The task performed was peg placement and was evaluated in a preliminary user study with five users.

In this paper, a novel repetitive control scheme is presented and discussed. The general framework is the control of repetitive tasks of robotic systems or, more in general, of automatic machines. The key idea of the proposed scheme consists in modifying the reference trajectory provided to the plant in order to compensate for external loads or unmodelled dynamics that cyclically affect it. By exploiting the dynamic filters for the B-spline trajectory planning, it has been possible to integrate the trajectory generation within a repetitive control scheme able to modify in real-time the reference signal with the aims of nullify interpolation errors. Experimental results obtained controlling two joints of a standard industrial manipulator are reported, showing the effectiveness of the proposed method.

This paper proposes a remote navigation system for a simple tele-presence robot. In general, robot functions of tele-presence robots are limited, and visual angle of the camera on robots is narrow, so they are unsuitable to use navigation services. The proposed system overcomes the difficulty by adopting system architecture in which robots are controlled remotely via a server located in the Internet, by using well-designed virtual reality techniques for robot control and by implementing almost all robot navigation functions into the server. In this paper, we also implemented Remote Open Campus System (ROCS) as a prototype system, and by using that, we confirmed the effectiveness and usefulness of the proposed system.

In order to make humans feeling comfortable when working with robots, it is necessary for robots to be as much as possible “human-like” in both their appearance and movements. In redundant manipulators, it is possible to use the additional degrees of freedom in order to make the robot motion more human-like, thus increasing the quality of the human-robot interaction. In this work, a redundancy resolution method to address this issue is presented. Such a method considers the human musculoskeletal system and a biomechanical model of the human upper limbs in order to define a strategy to solve the redundancy for a dual-arm anthropomorphic manipulator as a human would do, then making the robot able to both perform the prescribed task and to assume human-like postures.

Effective and stable execution of a remote manipulation task in an uncertain environment requires that the task force and position trajectories of the slave robot be appropriately commanded. To achieve this goal, in teleimpedance control, a reference command which consists of the stiffness and position profiles of the master is computed and realized by the compliant slave robot in real-time. This highlights the need for a suitable and computationally efficient tracking of the human limb stiffness profile in real-time. In this direction, based on the observations in human neuromotor control which give evidence on the predominant use of the arm configuration in directional adjustments of the endpoint stiffness profile, and the role of muscular co-activations which contribute to a coordinated regulation of the task stiffness in all directions, we propose a novel and computationally efficient model of the arm endpoint stiffness behaviour. Real-time tracking of the human arm kinematics is achieved using an arm triangle monitored by three markers placed at the shoulder, elbow and wrist level. In addition, a co-contraction index is defined using muscular activities of a dominant antagonistic muscle pair. Calibration and identification of the model parameters are carried out experimentally, using perturbation-based arm endpoint stiffness measurements in different arm configurations and co-contraction levels of the chosen muscles. Results of this study suggest that the proposed model enables the master to naturally execute a remote task by modulating the direction of the major axes of the endpoint stiffness and its volume using arm configuration and the co-activation of the involved muscles, respectively.

We consider the problem of computing the inverse dynamics of a serial robot manipulator with N elastic joints in a recursive numerical way. The solution algorithm is a generalized version of the standard Newton-Euler approach, running still with linear complexity O(N) but requiring to set up recursions that involve higher order derivatives of motion and force variables. Mimicking the case of rigid robots, we use this algorithm and a numerical factorization of the link inertia matrix (which needs to be inverted in the elastic joint case) for implementing on-line a feedback linearization control law for trajectory tracking purposes. The complete method has a complexity that grows as O(N3). The developed tools are generic, easy to use, and do not require symbolic Lagrangian modeling and customization, thus being of particular interest when the number N of elastic joints becomes large.

This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Five locomotion modes, including sitting, standing still, level-ground walking, ascending stairs, and descending stairs, are taken into consideration. The recognition is performed with locomotion information measured by the onboard hip angle sensors and the pressure insoles. These five modes are firstly divided into static modes and dynamic modes, and the two kinds are classified by monitoring the variation of the relative hip angles of the two legs within a pre-defined period. Static states are further classified into sitting and standing still based on the absolute hip angle. As for dynamic modes, a fuzzy-logic based method is proposed for the recognition. Two event-based locomotion features, including the hip joint angle at the first foot-strike and the center of foot pressure at the first foot-strike are used to calculate the membership of different modes based on the membership function, and the mode with the maximal membership is selected as the target mode. Experimental results with three subjects achieve an average recognition accuracy of 99.87% and average recognition delay of 18.12% of one gait cycle.

The state-of-the-art object pose estimation approaches represent the set of detected poses together with corresponding uncertainty. The inaccurate noisy poses may result in a configuration of overlapping objects especially in cluttered environments. Under a rigid body assumption the inter-penetrations between pairs of objects are geometrically inconsistent. In this paper, we propose the principle of minimum translation search, PROMTS, to find an inter-penetration-free configuration of the initially detected objects. The target application is to automate the task of unloading shipping containers, where a geometrically consistent configuration of objects is required for high level reasoning and manipulation. We find that the proposed approach to resolve geometrical inconsistencies improves the overall pose estimation accuracy. We examine the utility of two selected search methods: A-star and Depth-Limited search. The performance of the search algorithms are tested on data sets generated in simulation and from real-world scenarios. The results show overall improvement of the estimated poses and suggest that depth-limited search presents the best overall performance.

Enabling human-robot collaboration raises new challenges in safety-oriented robot design and control. Indices that quantitatively describe human injury due to a human-robot collision are needed to propose suitable pre-collision control strategies. This paper presents a novel model-based injury index built on the concept of dissipated kinetic energy in a potential inelastic impact. This quantity represents the fracture energy lost when a human-robot collision occurs, modeling both clamped and unclamped cases. It depends on the robot reflected mass and velocity in the impact direction. The proposed index is expressed in analytical form suitable to be integrated in a constraint-based pre-collision control strategy. The exploited control architecture allows to perform a given robot task while simultaneously bounding our injury assessment and minimizing the reflected mass in the direction of the impact. Experiments have been performed on a lightweight robot ABB FRIDA to validate the proposed injury index as well as the pre-collision control strategy.

This paper propose a practical and effective method for identifying the complete inertia parameters of a space robotic system. The key is the following steps: equivalent single-body identification, and equivalent two-body identification. For the former, all joints are locked into a normal configuration, and the thrusters are used for orbital maneuvering. The object function is defined from the view of acceleration and velocity. For the latter, only one joint is unlocked and driven to move along the exciting trajectory under the free-floating mode. The linear and angular momentum equations are used to define the object function. Hence, the parameter identification problem is transformed into a non-linear optimization problem, and the PSO algorithm is used to determine the optimal parameters. By sequentially unlocking the 1st to nth joint, the mass properties of body 0 to n are completely identified. The proposed method is general and can be easily extended for many cases.

We describe an experimental platform that uses an evolutionary algorithm to automatically tune the gains of a cascaded PID quadcopter controller. All parameters are tuned simultaneously, few platform assumptions are necessary, and no modeling is required. The platform is able to run back-to-back experiments for over 24 hours without human intervention. In a sample experiment, we apply the system to solve a hovering task — the behaviors generated by an initially-random population of gain vectors are evaluated and gradually improved, with the attainment of high fitness hover controllers reported within 12 hours.

We present a passive mechanism for quadrotor vehicles and other hover-capable aerial robots based on the cam-follower. This mechanism has two mating parts, one attached to the quadrotor and the other attached to a payload. These two parts are joined by a toggle switch—push to connect, push to disconnect—that is easy to activate with the quadrotor by varying thrust. We discuss the design parameters and provide an inertial model for our mechanism. With hardware experiments, we demonstrate the use of this passive mechanism to autonomously place a wireless camera in several different locations on the underside of a steel beam. Our mechanism is open source and can be easily fabricated with a 3D printer.

We consider the problem of organizing a scattered group of n robots in two-dimensional space. The communication graph of the swarm is connected, but there is no central authority for organizing it. We want to arrange them into a sorted and equally-spaced array between the robots with lowest and highest label, while maintaining a connected communication network. In this paper, we describe a distributed method to accomplish these goals, without using central control, while also keeping time, travel distance and communication cost at a minimum. We proceed in a number of stages (leader election, initial path construction, subtree contraction, geometric straightening, and distributed sorting), none of which requires a central authority, but still accomplishes best possible parallelization. The overall arraying is performed in O(n) time, O(n2) individual messages, and O(n) travel distance per robot. Implementation of the sorting and navigation use communication messages of fixed size, and are a practical solution for large populations of low-cost robots.

Automation of repetitive tasks can improve laparoscopic surgical procedures by unloading surgeons and reducing duration, trauma, and expense. However, surgical procedures involve delicate manipulation of deformable tissues in a very dynamic environment, suggesting that automated execution of surgical tasks should be carried out under the supervision of the surgeon. We propose a teleoperated architecture that allows a surgeon to employ and supervise agents that can autonomously perform or assist with surgical tasks. The architecture is independent of the automation method. It includes a dominance factor that allows the surgeon to take control over the slave robot at any time, and an aggressiveness factor that sets the performance pace of the autonomous agent. We tested the architecture during execution of a multilateral tension-and-cut task, where a human operator and an autonomous agent are responsible for tensioning or cutting of a tissue. The architecture allowed for supervised and paced automation of the task. We found that collaboration of the human operator and autonomous agent can lead to shorter completion time compared to performance of only a human.

This paper presents a novel variable transmission system that is based on the concept of digital hydraulics. In the proposed system, sets of rolling-diaphragm cylinders are mounted via different effective lever arms to an input and output joint. A variable subset of these cylinders is connected via three-way two-position on/off valves to a common hydraulic manifold. This introduces a controllable constraint on the hydraulic flow and creates a programmable hydraulic transmission. With three single-acting cylinders, we could realize 37 different transmission ratios. We investigated the nonholonomic flow constraint analytically, in simulation, and with an experimental prototype. Using water as fluid, we show that a very stiff transmission (124.2 Nm/rad) can be achieved within the range of ±6°. Theoretical transmission ratios are tracked with R-squared values of more than 0.996 and backlash is smaller than 1.4%. Furthermore, we show the applicability of the proposed transmission in the simulation of a body-powered knee-ankle exoskeleton.