Towards Developing Gripper to obtain Dexterous Manipulation

Artificial hands or grippers are essential elements in many robotic systems, such as, humanoid, industry, social robot, space robot, mobile robot, surgery and so on. As humans, we use our hands in different ways and can perform various maneuvers such as writing, altering posture of an object in-hand without having difficulties. Most of our daily activities are dependent on the prehensile and non-prehensile capabilities of our hand. Therefore, the human hand is the central motivation of grasping and manipulation, and has been explicitly studied from many perspectives such as, from the design of complex actuation, synergy, use of soft material, sensors, etc; however to obtain the adaptability to a plurality of objects along with the capabilities of in-hand manipulation of our hand in a grasping device is not easy, and not fully evaluated by any developed gripper. Industrial researchers primarily use rigid materials and heavy actuators in the design for repeatability, reliability to meet dexterity, precision, time requirements where the required flexibility to manipulate object in-hand is typically absent. On the other hand, anthropomorphic hands are generally developed by soft materials. However they are not deployed for manipulation mainly due to the presence of numerous sensors and consequent control complexity of under-actuated mechanisms that significantly reduce speed and time requirements of industrial demand. Hence, developing artificial hands or grippers with prehensile capabilities and dexterity similar to human like hands is challenging, and it urges combined contributions from multiple disciplines such as, kinematics, dynamics, control, machine learning and so on. Therefore, capabilities of artificial hands in general have been constrained to some specific tasks according to their target applications, such as grasping (in biomimetic hands) or speed/precision in a pick and place (in industrial grippers). Robotic grippers developed during last decades are mostly aimed to solve grasping complexities of several objects as their primary objective. However, due to the increasing demands of industries, many issues are rising and remain unsolved such as in-hand manipulation and placing object with appropriate posture. Operations like twisting, altering orientation of object within-hand, require significant dexterity of the gripper that must be achieved from a compact mechanical design at the first place. Along with manipulation, speed is also required in many robotic applications. Therefore, for the available speed and design simplicity, nonprehensile or dynamic manipulation is widely exploited. The nonprehensile approach however, does not focus on stable grasping in general. Also, nonprehensile or dynamic manipulation often exceeds robot\u2019s kinematic workspace, which additionally urges installation of high speed feedback and robust control. Hence, these approaches are inapplicable especially when, the requirements are grasp oriented such as, precise posture change of a payload in-hand, placing payload afterward according to a strict final configuration. Also, addressing critical payload such as egg, contacts (between gripper and egg) cannot be broken completely during manipulation. Moreover, theoretical analysis, such as contact kinematics, grasp stability cannot predict the nonholonomic behaviors, and therefore, uncertainties are always present to restrict a maneuver, even though the gripper is capable of doing the task. From a technical point of view, in-hand manipulation or within-hand dexterity of a gripper significantly isolates grasping and manipulation skills from the dependencies on contact type, a priory knowledge of object model, configurations such as initial or final postures and also additional environmental constraints like disturbance, that may causes breaking of contacts between object and finger. Hence, the property (in-hand manipulation) is important for a gripper in order to obtain human hand skill. In this research, these problems (to obtain speed, flexibility to a plurality of grasps, within-hand dexterity in a single gripper) have been tackled in a novel way. A gripper platform named Dexclar (DEXterous reConfigurable moduLAR) has been developed in order to study in-hand manipulation, and a generic spherical payload has been considered at the first place. Dexclar is mechanism-centric and it exploits modularity and reconfigurability to the aim of achieving within-hand dexterity rather than utilizing soft materials. And hence, precision, speed are also achievable from the platform. The platform can perform several grasps (pinching, form closure, force closure) and address a very important issue of releasing payload with final posture/ configuration after manipulation. By exploiting 16 degrees of freedom (DoF), Dexclar is capable to provide 6 DoF motions to a generic spherical or ellipsoidal payload. And since a mechanism is reliable, repeatable once it has been properly synthesized, precision and speed are also obtainable from them. Hence Dexclar is an ideal starting point to study within-hand dexterity from kinematic point of view. As the final aim is to develop specific grippers (having the above capabilities) by exploiting Dexclar, a highly dexterous but simply constructed reconfigurable platform named VARO-fi (VARiable Orientable fingers with translation) is proposed, which can be used as an industrial end-effector, as well as an alternative of bio-inspired gripper in many robotic applications. The robust four fingered VARO-fi addresses grasp, in-hand manipulation and release (payload with desired configuration) of plurality of payloads, as demonstrated in this thesis. Last but not the least, several tools and end-effectors have been constructed to study prehensile and non-prehensile manipulation, thanks to Bayer Robotic challenge 2017, where the feasibility and their potentiality to use them in an industrial environment have been validated. The above mentioned research will enhance a new dimension for designing grippers with the properties of dexterity and flexibility at the same time, without explicit theoretical analysis, algorithms, as those are difficult to implement and sometime not feasible for real system

Design & Implementation of a Low Cost Data Logger for Solar Home System

The demand of electric power is increasing gradually with the advancement of modern technology & engineering. Because the demand of electricity in urban areas or in industrial zones is large in amount & also more important than the rural areas, there exists a shortage of electric power supply facilities for rural households or remote location from the cities. In this case, Solar Energy is a promising solution to meet the demand for electricity services of rural areas in developing countries like Bangladesh. The effectiveness & stability of small PV systems for rural development is needed to be monitored for successful installment of Solar Panel. In order to analyze the system & modify it for cost reduction a data capturing unit should be constructed that can store the voltages & currents at three different terminals. A microcontroller operated Smart Data Logger can perform this work with high accuracy & precision maintaining the system cost much less than the conventional system. This paper deals with the design and implementation of a low cost data logger for solar home system. An experimental set up is designed and implemented and the paper illustrates the working principle, data observation and analysis, limitations, and future aspects of a low cost data logger for solar home system

Improving spatial agreement in machine learning-based landslide susceptibility mapping

Despite yielding considerable degrees of accuracy in landslide predictions, the outcomes of different landslide susceptibility models are prone to spatial disagreement; and therefore, uncertainties. Uncertainties in the results of various landslide susceptibility models create challenges in selecting the most suitable method to manage this complex natural phenomenon. This study aimed to propose an approach to reduce uncertainties in landslide prediction, diagnosing spatial agreement in machine learning-based landslide susceptibility maps. It first developed landslide susceptibility maps of Cox’s Bazar district of Bangladesh, applying four machine learning algorithms: K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM), featuring hyperparameter optimization of 12 landslide conditioning factors. The results of all the four models yielded very high prediction accuracy, with the area under the curve (AUC) values range between 0.93 to 0.96. The assessment of spatial agreement of landslide predictions showed that the pixel-wise correlation coefficients of landslide probability between various models range from 0.69 to 0.85, indicating the uncertainty in predicted landslides by various models, despite their considerable prediction accuracy. The uncertainty was addressed by establishing a Logistic Regression (LR) model, incorporating the binary landslide inventory data as the dependent variable and the results of the four landslide susceptibility models as independent variables. The outcomes indicated that the RF model had the highest influence in predicting the observed landslide locations, followed by the MLP, SVM, and KNN models. Finally, a combined landslide susceptibility map was developed by integrating the results of the four machine learning-based landslide predictions. The combined map resulted in better spatial agreement (correlation coefficients range between 0.88 and 0.92) and greater prediction accuracy (0.97) compared to the individual models. The modelling approach followed in this study would be useful in minimizing uncertainties of various methods and improving landslide predictions

The-state-of-the-art of soft robotics to assist mobility: a review of physiotherapist and patient identified limitations of current lower-limb exoskeletons and the potential soft-robotic solutions

Background: Soft, wearable, powered exoskeletons are novel devices that may assist rehabilitation, allowing users to walk further or carry out activities of daily living. However, soft robotic exoskeletons, and the more commonly used rigid exoskeletons, are not widely adopted clinically. The available evidence highlights a disconnect between the needs of exoskeleton users and the engineers designing devices. This review aimed to explore the literature on physiotherapist and patient perspectives of the longer-standing, and therefore greater evidenced, rigid exoskeleton limitations. It then offered potential solutions to these limitations, including soft robotics, from an engineering standpoint. Methods: A state-of-the-art review was carried out which included both qualitative and quantitative research papers regarding patient and/or physiotherapist perspectives of rigid exoskeletons. Papers were themed and themes formed the review’s framework. Results: Six main themes regarding the limitations of soft exoskeletons were important to physiotherapists and patients: safety; a one-size-fits approach; ease of device use; weight and placement of device; cost of device; and, specific to patients only, appearance of the device. Potential soft-robotics solutions to address these limitations were offered, including compliant actuators, sensors, suit attachments fitting to user’s body, and the use of control algorithms. Conclusions: It is evident that current exoskeletons are not meeting the needs of their users. Solutions to the limitations offered may inform device development. However, the solutions are not infallible and thus further research and development is required

Introduction of Bond Market: Would it be a possible Solution for Bangladesh?

This study aims at investigating the prospects of a bond market in Bangladesh. Most of the developed and developing economies have an active and successful bond market. But Bangladesh despite being one of the fastest-growing economies, does not have an active bond market. Hence, this study was designed to investigate the impact of a bond market on the economic growth of Asian countries and what are the prospects and challenges in Bangladesh. To investigate the benefits of a bond market in Bangladesh, this study examined the relationship between bond market return and economic growth of 4 Asian economies which included, India, Indonesia, Hong Kong, and Japan. The average annual yield of 10-year bonds was used as the independent variable and the annual GDP growth rate of these countries was used as the dependent variable in the econometric model. Data for the last 20 years from 2000 to 2019 were used for all the variables. The Unit Root Test showed that 3 variables were stationary at first difference and the other five variables were stationary at level. The Johansen Co-integration test identified the long-run association among the variables indicating the long-run relationship between bond market return and economic growth. Granger Causality revealed a bi-directional relationship for India; unidirectional relationship for Indonesia (Bond→GDP growth) and Japan (GDP Growth→Bond); and no unidirectional or bidirectional relationship among the bond market return and economic growth of Hong Kong. The various new projects, the overextension of the banking sector, and perhaps the overall good condition of the economy has created the perfect situation to develop a bond market in Bangladesh. As there are conditions that provide advantages in bond market creation, there are also various challenges that the government must overcome. Some of the most important challenges to clear up are the underdeveloped tax system, the illiquid or absent secondary market, the alternative source of debt, and the overall lack of investors. Considering the various developed bond markets these policy implications could seriously aid the development process

Creating a Sense of Presence in Remote Relationships : A concept of Calm Ambient artifact

Loneliness is a growing social problem that affects people from different age groups. Studies have shown that loneliness is prevalent more in young adults and the elderly demographic. Loneliness can pose serious health issues like cognitive malfunction, heart disease, stroke, depression, etc. People who stay alone from friends and family tend to feel lonelier. Conventional communication tools like a phone or video calls or using social media applications can help the users connect with people but also have adverse effects. As a result of this, the potential of an alternative nonverbal mode of communication needs to be explored. The research aims to understand individuals' behavior, traits, and hidden needs when it comes to loneliness. The purpose is to suggest an alternative way of communication that creates a sense of presence and ensures mental well for the people living alone and suffer from emotional loneliness. The concept of Calm and ambient technology has been explored in this thesis as an alternative means of communication. Users’ needs were gathered from eight semi-structured interviews, and two stakeholders were identified. Over forty ideas were generated from brainstorming. The ideas were sent to twenty individuals through snowballing. The response from them was analyzed and narrowed down by using concept screening and concept scoring. The final concept was a device called ‘One home lamp.’ The device uses light to show the presence of remote family members or loved ones to a person living alone. This concept product was then evaluated through ‘Mankoff’s heuristics’ to see its credibility as a calm ambient artifact