On periodically pendulum-diven systems for underactuated locomotion: a viscoelastic jointed model

This paper investigates the locomotion principles and nonlinear dynamics of the periodically pendulum-driven (PD) systems using the case of a 2-DOF viscoelastic jointed model. As a mechanical system with underactuation degree one, the proposed system has strongly coupled nonlinearities and can be utilized as a potential benchmark for studying complicated PD systems. By mathematical modeling and non-dimensionalization of the physical system, an insight is obtained to the global system dynamics. The proposed 2-DOF viscoelastic jointed model establishes a commendable interconnection between the system dynamics and the periodically actuated force. Subsequently, the periodic locomotion principles of the actuated subsystem are elaborately studied and synthesized with the characteristic of viscoelastic element. Then the analysis of qualitative changes is conducted respectively under the varying excitation amplitude and frequency. Simulation results validate the efficiency and performance of the proposed system comparing with the conventional system

Modelling and control of an elastically joint-actuated cart-pole underactuated system

This paper investigates the modelling and closedloop tracking control issues of a novel elastic underactuated multibody system. A torsional inverted pendulum cart-pole system with a single rotary actuator at the pivot of the cart is proposed. The system dynamics which incorporates with motion planning is firstly described. An optimization procedure is then discussed to plan the feasible trajectories that not just meet the performance requirements but also obtain optimality with respect to the cart displacement and average velocity. A closed-loop tracking controller is designed under collocated partial feedback linearization (CPFL). Subsequent presentation of simulation demonstrates that the proposed system is promising as compared to the previous work. The paper concludes with the application of our novel scheme to the design and control of autonomous robot systems

Modelling, dynamic analysis and control of capsubot systems with stable propulsion for medical and recovery assistances

The growth of medical robots since the mid-1980s has been striking. From a few initial efforts in stereotactic brain surgery, orthopaedics, endoscopic surgery, microsurgery, and other areas, the field has expanded to include commercially marketed, clinically deployed systems, and a robust and exponentially expanding research community. Obscure gastrointestinal (GI) bleeding, Crohn disease, Celiac disease, small bower tumors, and other disorders that occur in the GI tract have always been challenging to be diagnosed and treated due to the inevitable difficulty in accessing such a complex environment within the human body. Robot-assisted minimally invasive surgery has become an choice

Geometric techniques for trajectory planning and chaos control of a bio-inspired autogenetic capsule robot

Biological systems achieve energy efficient and adaptive behaviours through extensive internal and external compliance interactions. Active dynamic compliance are created and enhanced from musculoskeletal system (joint-space) to external environment (task-space) amongst the underactuated motions. The terminology bio-inspiration implies the understanding of fundamental principles underlying the motion behaviours of animals and humans and transfers these principles into the development of robotic systems. For example, during walking, the muscles constantly change their stiffness and damping when the leg is swinging forward and the foot is put on the ground. This idea enables the exploration in robotic systems with flexible elements—viscoelasticity to mimic the compliant motion of biological muscles. Underactuated systems with viscoelastic actuation are similar to these biological systems, in that their self-organisation and overall tasks must be achieved by coordinating the subsystems and dynamically interacting with the environment

Robot-assisted smart firefighting and interdisciplinary perspectives

Urbanization and changes in modern infrastructure have introduced new challenges to current firefighting practices. The current manual operations and training including fire investigation, hazardous chemicals detection, fire and rescue are insufficient to protect the firefighter's safety and life. The firefighting and rescue functions of the existing equipment and apparatus and their dexterity are limited, particularly in the harsh firefighting environments. It is well-established that data and informatics are key factors for efficient and smart firefighting operation. This paper provides a review on the robot-assisted firefighting systems with interdisciplinary perspectives to identify the needs, requirements, challenges as well as future trends to facilitate smart and efficient operations. The needs and challenges of robot-assisted firefighting systems are firstly investigated and identified. Subsequently, prevailing firefighting robotic platforms in literature as well as in practices are elaborately scrutinized and discussed, followed by investigation of localization and navigation support methods. Finally, conclusions and future trends outlook are provided

Usability evaluation of assistive technologies through qualitative research focusing on people with mild dementia

The assistive technologies (ATs) are commonly used for the wellbeing of people with dementia (PWD). Research shows that current ATs are not performing to their best and high rate of AT abandonment still exist. Although empirical evaluations greatly impact AT success, yet only few studies investigated AT usability for PWD. To the best of authors knowledge there is no AT usability evaluation study conducted in the South Asia. Therefore a qualitative study is carried out to identify which AT factors encourage and discourage the PWD through semi-structured interviews. Thematic analysis is used to generate themes and sub-themes. The (happy users, non-happy users and technology and human care) emerged as three main themes while, (communication, monitoring and reminders) as popular AT types. Most PWD use ATs for socialization and health monitoring. Overall the PWD appreciated the role of ATs in their lives, but showed concerns about interface efficacy, function simplicity and elderly requirements adaptation. The already met and unmet needs of the PWD are also investigated. The AT producers should make user interface simpler and tailor future ATs to the specific requirements of the PWD. The user centered techniques should be adopted for the development of new ATs

A survey on wearable sensor modality centred human activity recognition in health care

Increased life expectancy coupled with declining birth rates is leading to an aging population structure. Aging-caused changes, such as physical or cognitive decline, could affect people's quality of life, result in injuries, mental health or the lack of physical activity. Sensor-based human activity recognition (HAR) is one of the most promising assistive technologies to support older people's daily life, which has enabled enormous potential in human-centred applications. Recent surveys in HAR either only focus on the deep learning approaches or one specific sensor modality. This survey aims to provide a more comprehensive introduction for newcomers and researchers to HAR. We first introduce the state-of-art sensor modalities in HAR. We look more into the techniques involved in each step of wearable sensor modality centred HAR in terms of sensors, activities, data pre-processing, feature learning and classification, including both conventional approaches and deep learning methods. In the feature learning section, we focus on both hand-crafted features and automatically learned features using deep networks. We also present the ambient-sensor-based HAR, including camera-based systems, and the systems which combine the wearable and ambient sensors. Finally, we identify the corresponding challenges in HAR to pose research problems for further improvement in HAR

Design, modelling and control of a capsule robot with hybrid propulsions for medical inspections and assistances

The growth of medical robots since the mid-1980s has been striking. From a few initial efforts in stereotactic brain surgery, orthopaedics, endoscopic surgery, microsurgery, and other areas, the field has expanded to include commercially marketed, clinically deployed systems, and a robust and exponentially expanding research community. Obscure gastrointestinal (GI) bleeding, Crohn disease, Celiac disease, small bower tumors, and other disorders that occur in the GI tract have always been challenging to be diagnosed and treated due to the inevitable difficulty in accessing such a complex environment within the human body. Robot-assisted minimally invasive surgery has become an choice

Mutual information inspired feature selection using kernel canonical correlation analysis

This paper proposes a filter-based feature selection method by combining the measurement of kernel canonical correlation analysis (KCCA) with the mutual information (MI)-based feature selection method, named mRMJR-KCCA. The mRMJR-KCCA maximizes the relevance between the feature candidate and the target class labels and simultaneously minimizes the joint redundancy between the feature candidate and the already selected features in the view of KCCA. To improve the computation efficiency, we adopt the Incomplete Cholesky Decomposition to approximate the kernel matrix in implementing the KCCA in mRMJR-KCCA for larger-size datasets. The proposed method is experimentally evaluated on 13 classification-associated datasets. Compared with certain popular feature selection methods, the experimental results demonstrate the better performance of the proposed mRMJR-KCC