Juan C. Fraile

Optimization of collision free trajectories in multi-robot systems

This work describes a path planning method applied to a three robot system. Trajectories are optimized to allow minimum time performance of the overall system. Mathematical programming methods with a global approach are used.

Comparative analysis of collision-free path-planning methods for multi-manipulator systems

Motion planning for manipulators with many degrees of freedom is a complex task. The research in this area has been mostly restricted to static environments. This paper presents a comparative analysis of three reactive on-line path-planning methods for manipulators: the elastic-strip, strategy-based and potential field methods. Both the elastic-strip method [O. Brock and O. Khatib, “Elastic strips: A framework for integrated planning and execution,” Int. Symp. Exp. Robot. 245–254 (1999)] and the potential field method [O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” Int. J. Robot. Res. 5(1), 90–98 (1986)] have been adapted by the authors to the problem at hand related to our multi-manipulator system (MMS) (three manipulators with five degrees of freedom each). Strategy-based method is an original contribution by the authors [M. Mediavilla, J. L. Gonzalez, J. C. Fraile and J. R. Peran, “Reactive approach to on-line path planning for robot manipulators in dynamic environments,” Robotica 20, 375–384 (2002); M. Mediavilla, J. C. Fraile, T. Gonzalez and I. J. Galindo, “Selection of strategies for collision-free motion in multi-manipulator systems,” J. Intell. Robot Syst 38, 85–104 (2003)].The three methods facilitate on-line path planning for our MMS in dynamic environments with collision avoidance, where the three manipulators may move at the same time in their common workspace. We have defined some ‘basic motion problems’ for the MMS, and a series of simulations has been running that will tell us how effective each path-planning method is. The simulations have been performed and the obtained results have been analysed by using a software program developed by the authors.The paper also presents experimental results obtained applying the path-planning methods to our MMS, that perform pick-and-place tasks sharing common working areas.

Online motion planning for robotic arms: new approach based on the reduction of the search space

This paper presents a new method for online path planning for robotic arms in dynamic environments. Most online path planning methods are based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). The method presented in this paper avoids local minima by using a two stage framework. The robots react to dynamic environments using a local and reactive planning method restricted to a subset of its configuration space. Since the subset has few degrees of freedom the computational cost of the online stage is very low. An off-line stage chooses the subset of the configuration space that minimizes the probability of blockades and inefficient motions.

E2Rebot: A robotic platform for upper limb rehabilitation in patients with neuromotor disability

The use of robotic platforms for neuro-rehabilitation may boost the neural plasticity process and improve motor recovery in patients with upper limb mobility impairment as a consequence of an acquired brain injury. A robotic platform for this aim must provide ergonomic and friendly design, human safety, intensive task-oriented therapy, and assistive forces. Its implementation is a complex process that involves new developments in the mechanical, electronics, and control fields. This article presents the end-effector rehabilitation robot, a 2-degree-of-freedom planar robotic platform for upper limb rehabilitation in patients with neuromotor disability after a stroke. We describe the ergonomic mechanical design, the system control architecture, and the rehabilitation therapies that can be performed. The impedance-based haptic controller implemented in end-effector rehabilitation robot uses the information provided by a JR3 force sensor to achieve an efficient and friendly patient–robot interaction. Two task-oriented therapy modes have been implemented based on the “assist as needed” paradigm. As a result, the amount of support provided by the robot adapts to the patient’s requirements, maintaining the therapy as intensive as possible without compromising the patient’s health and safety and promoting engagement.

Reactive approach to on-line path planning for robot manipulators in dynamic environments

Path planning for robot manipulators is a complex subject, which is why most research has been restricted to static environments, where off-line path planning is acceptable, and very little work has been done on dynamic environments. On-line path planning is normally based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). In this paper we present a new method for on-line path planning in dynamic environments. It solves the lack of global vision of local methods by using a hybrid two stage framework that combines global and local planning.

REACTIVE PATH PLANNING FOR ROBOTIC ARMS WITH MANY DEGREES OF FREEDOM IN DYNAMIC ENVIRONMENTS

Abstract It is well known that path planning for robots with many degrees of freedom is a complex task. That is the reason why the research on this area has been mostly restricted to static environments. This paper presents a new method for on-line path planning for robotic arms in dynamic environments. Most on-line path planning methods are based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). The method presented in this paper avoids local minima by using a two stage framework. The robots react to dynamic environments using a local and reactive planning method restricted to a subset of its configuration space. Since the subset has few degrees of freedom the computational cost of the on-line stage is very low. An off-line stage chooses the subset of the configuration space that minimizes the probability of blockades and inefficient motions.

Influences of robot maintenance and failures in the performance of a multirobot system

In a multirobot system (MRS) several robots can operate simultaneously on the same product, and allow the accomplishment of tasks that a single robot could not approach due to restrictions associated to the product and/or the robot. We propose a MRS consisting of three robots and four different working platforms, that allows the characteristics of joint operation to be maintained even if a robot is out of service. In order to make a detailed analysis of the operating characteristics of the MRS we propose to use timed Petri nets (GSPN and DSPN), than allow the efficiency of the system to be evaluated. This paper analyses the influence of the robot maintenance and failures on the throughput of an MRS, under different conditions of operative configuration, number of subtasks, degree of interference, operation mode on the product, etc.

Transnational lifelong education course in robotic systems

Robotics constitutes a multidisciplinary area, congregating knowledge from different scientific domains. The learning of robotic systems requires the acquisition of multidisciplinary scientific bases, and high integration and synthesis abilities, which is not an easy task. This paper describes the implementation of a lifelong course that aims to provide a global insight on robotics field, introducing the concepts and technologies for different domain applications, namely industrial robotics, autonomous mobile robotics and robotics applied in medicine. This is accomplished in an international framework where individual knowledge and experiences will be confronted in a multidisciplinary level and intercultural environment.

Characterization of Hand Movements using a Sensing Glove in Hand Assisted Laparoscopic Surgery

The past thirty years have seen increasingly rapid advances in the field of laparoscopic surgery, in part because of the use of robots. A well-known example is the da Vinci surgical system. However, far too little attention has been paid to Hand Assisted Laparoscopic Surgery (HALS), a surgery in which the surgeon introduces the non-dominant hand into the abdomen of the patient. The risk of collision between the hand of the surgeon and the tool moved by the robot is the reason why these robots for laparoscopic surgery are not appropriate for HALS. On the other hand, in recent years, there has been an increasing interest in wearables, which have been introduced in our daily life. This interest and the lack of surgery robots for HALS are the reasons to develop a sensing glove which co-works with a collaborative robot in this kind of surgery. The aim of this paper is to study the use of a sensing glove which will provide information of the movements of the surgeons hand to the collaborative robot. This information determinates the actions that the robot will carry on. The first step was to define different movements of the hand which could be identified. An algorithm identifies these movements using the data given by the sensing glove. For the purpose of algorithm accuracy measurement, 4 persons wearing the sensing glove made a sequence with different movements. The evidence from this study suggests that a sensing glove can be used to send information of the movements of the surgeons hand to a collaborative robot during a HALS.

Collaborative Robotic System for Hand-Assisted Laparoscopic Surgery

Hand-assisted laparoscopic surgery is a Minimally Invasive Surgery technique that is based on the insertion of one surgeon’s hand inside the abdominal cavity. In this scenario, a robotic assistant can properly collaborate with the surgeon, working side by side with him/her. This paper presents a robotic system for this kind of technique, based on a cognitive architecture that makes possible an efficient collaboration with the surgeon, thanks to a better understanding of the environment and the learning mechanisms included. This architecture includes a hand gesture recognition module and two different autonomous movement of the robotic arms, one for the camera motion and the other for the tool movement. All of these modules take advantage of the cognitive learning mechanisms of the architecture, fitting their behavior to the current user and procedure.