Alberto Jardón Huete

The MATS robot: service climbing robot for personal assistance

The human care and service field requires an innovative robotic solution to make the daily care of elderly and disabled people in both home and workplace environments easier. The European Union (EU) project MATS (flexible mechatronic assistive technology system) has developed a new concept of a climbing robot for this type of service application. The climbing process is performed by moving the robot between very simple docking stations (DSs) placed in the environment. The MATS climbing robot is a symmetrical, five degrees of freedom (5 DOF), self-containing manipulator that includes all the control and communication systems on board. To fulfil the climbing movements successfully, the developed robot is lightweight, about 11 kg for a 1.3 m reach. This article presents real experiments conducted with the robot during its climbing movements and assistance tasks for disabled persons.

Personal Autonomy Rehabilitation in Home Environments by a Portable Assistive Robot

Increasingly disabled and elderly people with mobility problems want to live autonomously in their home environment. They are motivated to use robotic aids to perform tasks by themselves, avoiding permanent nurse or family assistant supervision. They must find means to rehabilitate their abilities to perform daily life activities (DLAs), such as eating, shaving, or drinking. These means may be provided by robotic aids that incorporate possibilities and methods to accomplish common tasks, aiding the user in recovery of partial or complete autonomy. Results are highly conditioned by the systems usability and potential. The developed portable assistive robot ASIBOT helps users perform most of these tasks in common living environments. Minimum adaptations are needed to provide the robot with mobility throughout the environment. The robot can autonomously climb from one surface to another, fixing itself to the best place to perform each task. When the robot is attached to its wheelchair, it can move along with it as a bundle. This paper presents the work performed with the ASIBOT in the area of rehabilitation robotics. First, a brief description of the ASIBOT system is given. A description of tests that have been performed with the robot and several impaired users is given. Insight into how these experiences have influenced our research efforts, especially, in home environments, is also included. A description of the test bed that has been developed to continue research on performing DLAs by the use of robotic aids, a kitchen environment, is given. Relevant conclusions are also included.

Adaptive collision-limitation behavior for an assistive manipulator

An approach for adaptive shared control of an assistive manipulator is presented. A set of distributed collision and proximity sensors is used to aid in limiting collisions during direct control by the disabled user. Artificial neural networks adapt the use of the proximity sensors online, which limits movements in the direction of an obstacle before a collision occurs. The system learns by associating the different proximity sensors to the collision sensors where collisions are detected. This enables the user and the robot to adapt simultaneously and in real-time, with the objective of converging on a usage of the proximity sensors that increases performance for a given user, robot implementation and task-set. The system was tested in a controlled setting with a simulated 5 DOF assistive manipulator and showed promising reductions in the mean time on simplified manipulation tasks. It extends earlier work by showing that the approach can be applied to full multi-link manipulators.

Benchmarking shared control for assistive manipulators: From controllability to the speed-accuracy trade-off

Assistive robots are increasingly being envisioned as an aid to the elderly and disabled. However controlling a robotic system with a potentially large amount of Degrees of Freedom (DOF) in a safe and reliable way is not an easy task, even without limitations in the mobility of the upper extremities. Shared control has been proposed as a way of aiding disabled users in controlling mobility aids such as assistive wheelchairs, by using the sensors of the robotic platform to predict the users intent and assist in navigation. Assistive manipulators, that aim to perform physical Daily Life Activities (DLA), is a more complex problem however. This calls for good experimental practices to ensure repeatability, reproducibility, and steady progress. The work presented here attempts to model the complete system for assistive manipulators, and in the context of this model define metrics and good practices for benchmarking shared control for such robots. An adaptive shared control approach for limiting collisions during teleoperation is used as a case study. Improvements in performance are shown, quantified by the trade-off between mean time and number of collisions as well as the controllability from the users perspective.

Distributed and Adaptive Shared Control Systems: Methodology for the Replication of Experiments

Much work in robotics aimed at real-world applications falls in the large segment between teleoperated and fully autonomous systems. Such systems are characterized by the close coupling between the human operator and the robot, in principle, allowing the agents to share their particular sensing, adaptation, and decision-making capabilities. Replicable experiments can advance the state of the art of such systems but pose practical and epistemological challenges. For example, the trajectory of the system is governed by the adaptation both in the human and the robot agent. What do we need besides (or instead of) data sets for such a system? The degree of similarity between comparable experiments and the exact meaning of replication need to be clarified. Here, we explore replication of a distributed and adaptive shared control for an assistive robot manipulator. We attempt a methodological approach for reporting two virtual human experiments on the system: modeling the complete human-robot binomial, deriving closedloop performance metrics from the models, and openly publishing the results and experiment implementations.

Distributed Sensing, Learning and Control in an Assistive Manipulator

One of the grand challenges for the robotics community is to create robots that operate robustly in realworld scenarios. Most current robots are limited to factories, laboratories or similar controlled settings. This contrasts with the seeming ease with which insects, animals and humans handle uncertainty, dynamic events and complexity. Assistive robots are for example being envisioned for aiding elderly and disabled persons in their homes. A key skill for these robots will be to operate in, and physically manipulate, daily life environments. However, it is unclear how to achieve this while complying with the safety and reliability requirements of such devices. Distributed Adaptive Control (DAC) is an example of a biologically inspired architecture for control and adaptation, where the lowest unit is the reflex. We here explore recent work on extending this idea to shared control of assistive robot manipulators. That is, where sensing, learning and control are distributed throughout the system, and across both user and robot. We show that such a distributed approach can reduce the need for central information processing, exact internal representations, and “global” approaches to learning in the robot. The reduced algorithmic complexity can help increase the robustness and usability of the system on real-world tasks.

An information-theoretic approach to modeling and quantifying assistive robotics HRI

Assistive robotics HRI has a number of important characteristics that distinguishes it from other forms of HRI. This includes the need for both high flexibility, safety and reliability in controlling the robotic system. Approaching the system as a human-robot binomial, with the user and the robot acting in a closed-loop, may be beneficial to understanding and improving the interaction. This paper investigates the feasibility of modeling and quantifying assistive robotics HRI inside such a human-robot binomial using concepts from Information Theory.

Human Centered Mechatronics

Mechatronics is an applied interdisciplinary science that aims to integrate mechanical elements, electronics and parts of biological organisms. Mechatronics’ end goal is to design useful products. When those products are focused in human welling, helping them or by restoring lost capabilities, any mechatronics solution should consider at the beginning of the design process that all the mechanics, control and electronics must work cooperatively with and for human. Several challenges related to control issues and the role of human and machine in the control loop could be better achieved if human centered mechanical design approaches are assumed. From a mechanical point of view the development of robots that could operate in close interaction with human is a big challenge. Soft human–robot interaction is the branch that covers those topics. To analyze this fact, in this chapter, a general classification of the different types of robotic systems that currently could be found as well as actuators commonly used. The safety of the robotic assistant, working in close cooperation with humans, is currently a topic of interest in the robotics community. There are many ways to design and conduct intrinsically safe systems, from those that use complex sensory systems to monitor the user within the working environment to avoid contact, even the most sophisticated seeking to minimize the inertia of its moving parts (links) in order to reduce damage in case of accidental collision. Safety mechanisms will be reviewed based on variable stiffness actuators, novel designs of all-gear-motor shaft, etc. The study will include risk assessment and safety for the user. Risk and safety standards will be reviewed. Taking into account undesired collision, two types of safety strategies are reported: pre-contact and post-contact strategies. The first minimize the possible effect of the accident before it occurs. The latter should minimize the consequences of that accident. Those new advances in the design techniques are being applied for ultra-light weight robotics arms and also prosthesis combined with new solutions in kinematic synthesis, materials, geometry and shape of mechanical components, actuators technologies and new thermal and FEM analysis techniques to validate them.