A Service Robot for Navigation Assistance and Physical Rehabilitation of Seniors

The population of the advanced countries is ageing, with the direct consequence that an increasing number of people will have to live with sensitive, cognitive and physical disabilities. People with impaired physical ability are not confident to move alone, especially in crowded environment and for long journeys, highly reducing the quality of their life. We propose a new generation of robotic walking assistants whose mechanical and electronic components are conceived to optimize the collaboration between the robot and its users. We will apply these general ideas to investigate the interaction between older adults and a robotic walker, named FriWalk, exploiting it either as a navigational or as a rehabilitation aid. For the use of the FriWalk as a navigation assistance, the system guides the user securing high levels of safety, a perfect compliance with the social rules and non-intrusive interaction between human and machine. To this purpose, we developed several guidance systems ranging from completely passive strategies to active solutions exploiting either the rear or the front motors mounted on the robot. The common strategy at the basis of all the algorithms is that the responsibility of the locomotion belongs always to the user, both to increase the mobility of elder users and to enhance their perception of control over the robot. This way the robot intervenes only whenever it is strictly necessary not to mitigate the user safety. Moreover, the robotic walker has been endowed with a tablet and graphical user interface (GUI) which provides the user with the visual indications about the path to follow. Since the FriWalk was developed to suit the needs of users with different deficits, we conducted extensive human-robot interaction (HRI) experiments with elders, complemented with direct interviews of the participants. As concerns the use of the FriWalk as a rehabilitation aid, force sensing to estimate the torques applied by the user and change the user perceived inertia can be exploited by doctors to let the user feel the device heavier or lighter. Moreover, thanks to a new generation of sensors, the device can be exploited in a clinical context to track the performance of the users' rehabilitation exercises, in order to assist nurses and doctors during the hospitalization of older adults

Authority-Sharing Control of Assistive Robotic Walkers

A recognized consequence of population aging is a reduced level of mobility, which undermines the life quality of several senior citizens. A promising solution is represented by assisitive robotic walkers, combining the benefits of standard walkers (improved stability and physical support) with sensing and computing ability to guarantee cognitive support. In this context, classical robot control strategies designed for fully autonomous systems (such as fully autonomous vehicles, where the user is excluded from the loop) are clearly not suitable, since the user’s residual abilities must be exploited and practiced. Conversely, to guarantee safety even in the presence of user’s cognitive deficits, the responsibility of controlling the vehicle motion cannot be entirely left to the assisted person. The authority-sharing paradigm, where the control authority, i.e., the capability of controlling the vehicle motion, is shared between the human user and the control system, is a promising solution to this problem. This research develops control strategies for assistive robotic walkers based on authority-sharing: this way, we ensure that the walker provides the user only the help he/she needs for safe navigation. For instance, if the user requires just physical support to reach the restrooms, the robot acts as a standard rollator; however, if the user’s cognitive abilities are limited (e.g., the user does not remember where the restrooms are, or he/she does not recognize obstacles on the path), the robot also drives the user towards the proper corridors, by planning and following a safe path to the restrooms. The authority is allocated on the basis of an error metric, quantifying the distance between the current vehicle heading and the desired movement direction to perform the task. If the user is safely performing the task, he/she is endowed with control authority, so that his/her residual abilities are exploited. Conversely, if the user is not capable of safely solving the task (for instance, he/is going to collide with an obstacle), the robot intervenes by partially or totally taking the control authority to help the user and ensure his/her safety (for instance, avoiding the collision). We provide detailed control design and theoretical and simulative analyses of the proposed strategies. Moreover, extensive experimental validation shows that authority-sharing is a successful approach to guide a senior citizen, providing both comfort and safety. The most promising solutions include the use of haptic systems to suggest the user a proper behavior, and the modification of the perceived physical interaction of the user with the robot to gradually share the control authority using a variable stiffness vehicle handling

Fuzzy optimisation based symbolic grounding for service robots

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySymbolic grounding is a bridge between task level planning and actual robot sensing and actuation. Uncertainties raised by unstructured environments make a bottleneck for integrating traditional artificial intelligence with service robotics. In this research, a fuzzy optimisation based symbolic grounding approach is presented. This approach can handle uncertainties and helps service robots to determine the most comfortable base region for grasping objects in a fetch and carry task. Novel techniques are applied to establish fuzzy objective function, to model fuzzy constraints and to perform fuzzy optimisation. The approach does not have the short comings of others’ work and the computation time is dramatically reduced in compare with other methods. The advantages of the proposed fuzzy optimisation based approach are evidenced by experiments that were undertaken in Care-O-bot 3 (COB 3) and Robot Operating System (ROS) platforms

Human aware robot navigation

Abstract. Human aware robot navigation refers to the navigation of a robot in an environment shared with humans in such a way that the humans should feel comfortable, and natural with the presence of the robot. On top of that, the robot navigation should comply with the social norms of the environment. The robot can interact with humans in the environment, such as avoiding them, approaching them, or following them. In this thesis, we specifically focus on the approach behavior of the robot, keeping the other use cases still in mind. Studying and analyzing how humans move around other humans gives us the idea about the kind of navigation behaviors that we expect the robots to exhibit. Most of the previous research does not focus much on understanding such behavioral aspects while approaching people. On top of that, a straightforward mathematical modeling of complex human behaviors is very difficult. So, in this thesis, we proposed an Inverse Reinforcement Learning (IRL) framework based on Guided Cost Learning (GCL) to learn these behaviors from demonstration. After analyzing the CongreG8 dataset, we found that the incoming human tends to make an O-space (circle) with the rest of the group. Also, the approaching velocity slows down when the approaching human gets closer to the group. We utilized these findings in our framework that can learn the optimal reward and policy from the example demonstrations and imitate similar human motion

Combining motion planning with social reward sources for collaborative human-robot navigation task design

Across the human history, teamwork is one of the main pillars sustaining civilizations and technology development. In consequence, as the world embraces omatization, human-robot collaboration arises naturally as a cornerstone. This applies to a huge spectrum of tasks, most of them involving navigation. As a result, tackling pure collaborative navigation tasks can be a good first foothold for roboticists in this enterprise. In this thesis, we define a useful framework for knowledge representation in human-robot collaborative navigation tasks and propose a first solution to the human-robot collaborative search task. After validating the model, two derived projects tackling its main weakness are introduced: the compilation of a human search dataset and the implementation of a multi-agent planner for human-robot navigatio

European regulatory framework for person carrier robots

The aim of this paper is to establish the grounds for a future regulatory framework for Person Carrier Robots, which includes legal and ethical aspects. Current industrial standards focus on physical human–robot interaction, i.e. on the prevention of harm. Current robot technology nonetheless challenges other aspects in the legal domain. The main issues comprise privacy, data protection, liability, autonomy, dignity, and ethics. The paper first discusses the need to take into account other interdisciplinary aspects of robot technology to offer complete legal coverage to citizens. As the European Union starts using impact assessment methodology for completing new technologies regulations, a new methodology based on it to approach the insertion of personal care robots will be discussed. Then, after framing the discussion with a use case, analysis of the involved legal challenges will be conducted. Some concrete scenarios will contribute to easing the explanatory analysis

New Updates in E-Learning

This book presents state-of-the-art educational technologies and teaching methodologies and discusses future educational philosophies in support of the global academic society. New Updates in E-Learning is a collection of chapters addressing important issues related to effective utilization of the Internet and Cloud Computing, virtual robotics, and real-life application of hybrid educational environments to enhance student learning regardless of geographical location or other constraints. Over ten chapters, the book discusses the current and future evolution of educational technologies and methodologies and the best academic practices in support of providing high-quality education at all academic levels

The development of assistive technology to reveal knowledge of physical world concepts in young people who have profound motor impairments.

Cognitively able children and young people who have profound motor impairments and complex communication needs (the target group or TG) face many barriers to learning, communication, personal development, physical interaction and play experiences, compared to their typically developing peers. Physical interaction (and play) are known to be important components of child development, but this group currently has few suitable ways in which to participate in these activities. Furthermore, the TG may have knowledge about real world physical concepts despite having limited physical interaction experiences but it can be difficult to reveal this knowledge and conventional assessment techniques are not suitable for this group, largely due to accessibility issues. This work presents a pilot study involving a robotics-based system intervention which enabled members of the TG to experience simulated physical interaction and was designed to identify and develop the knowledge and abilities of the TG relating to physical concepts involving temporal, spatial or movement elements. The intervention involved the participants using an eye gaze controlled robotic arm with a custom made haptic feedback device to complete a set of tasks. To address issues with assessing the TG, two new digital Assistive Technology (AT) accessible assessments were created for this research, one using static images, the other video clips. Two participants belonging to the TG took part in the study. The outcomes indicated a high level of capability in performing the tasks, with the participants exhibiting a level of knowledge and ability which was much higher than anticipated. One explanation for this finding could be that they have acquired this knowledge through past experiences and ‘observational learning’. The custom haptic device was found to be useful for assessing the participants’ sense of ‘touch’ in a way which is less invasive than conventional ‘pin-prick’ techniques. The new digital AT accessible assessments seemed especially suitable for one participant, while results were mixed for the other. This suggests that a combination of ‘traditional’ assessment and a ‘practical’ intervention assessment approach may help to provide a clearer, more rounded understanding of individuals within the TG. The work makes contributions to knowledge in the field of disability and Assistive Technology, specifically regarding: AT accessible assessments; haptic device design for the TG; the combination of robotics, haptics and eye gaze for use by the TG to interact with the physical world; a deeper understanding of the TG in general; insights into designing for and working with the TG. The work and information gathered can help therapists and education staff to identify strengths and gaps in knowledge and skills, to focus learning and therapy activities appropriately, and to change the perceptions of those who work with this group, encouraging them to broaden their expectations of the TG