Innovative robot hand designs of reduced complexity for dexterous manipulation

This thesis investigates the mechanical design of robot hands to sensibly reduce the system complexity in terms of the number of actuators and sensors, and control needs for performing grasping and in-hand manipulations of unknown objects. Human hands are known to be the most complex, versatile, dexterous manipulators in nature, from being able to operate sophisticated surgery to carry out a wide variety of daily activity tasks (e.g. preparing food, changing cloths, playing instruments, to name some). However, the understanding of why human hands can perform such fascinating tasks still eludes complete comprehension. Since at least the end of the sixteenth century, scientists and engineers have tried to match the sensory and motor functions of the human hand. As a result, many contemporary humanoid and anthropomorphic robot hands have been developed to closely replicate the appearance and dexterity of human hands, in many cases using sophisticated designs that integrate multiple sensors and actuators---which make them prone to error and difficult to operate and control, particularly under uncertainty. In recent years, several simplification approaches and solutions have been proposed to develop more effective and reliable dexterous robot hands. These techniques, which have been based on using underactuated mechanical designs, kinematic synergies, or compliant materials, to name some, have opened up new ways to integrate hardware enhancements to facilitate grasping and dexterous manipulation control and improve reliability and robustness. Following this line of thought, this thesis studies four robot hand hardware aspects for enhancing grasping and manipulation, with a particular focus on dexterous in-hand manipulation. Namely: i) the use of passive soft fingertips; ii) the use of rigid and soft active surfaces in robot fingers; iii) the use of robot hand topologies to create particular in-hand manipulation trajectories; and iv) the decoupling of grasping and in-hand manipulation by introducing a reconfigurable palm. In summary, the findings from this thesis provide important notions for understanding the significance of mechanical and hardware elements in the performance and control of human manipulation. These findings show great potential in developing robust, easily programmable, and economically viable robot hands capable of performing dexterous manipulations under uncertainty, while exhibiting a valuable subset of functions of the human hand.Open Acces

Grasping Angle Estimation of Human Forearm with Underactuated Grippers Using Proprioceptive Feedback

In this paper, a method for the estimation of the angle of grasping of a human forearm, when grasped by a robot with an underactuated gripper, using proprioceptive information only, is presented. Knowing the angle around the forearm’s axis (i.e. roll angle) is key for the safe manipulation of the human limb and biomedical sensor placement among others. The adaptive gripper has two independent underactuated fingers with two phalanges and a single actuator each. The final joint position of the gripper provides information related to the shape of the grasped object without the need for external contact or force sensors. Regression methods to estimate the roll angle of the grasping have been trained with forearm grasping information from different humans at each angular position. The results show that it is possible to accurately estimate the rolling angle of the human arm, for trained and unknown people.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Design of a partially-coupled self-adaptive robotic finger optimized for collaborative robots

This paper presents the design and optimization of a self-adaptive, a.k.a. underactuated, finger targeted to be used with collaborative robots. Typical robots, whether collaborative or not, mostly rely on standard translational grippers for pick-and-place operations. These grippers are constituted from an actuated motion platform on which a set of jaws is rigidly attached. These jaws are often designed to secure a precise and limited range of objects through the application of pinching forces. In this paper, the design of a self-adaptive robotic finger is presented which can be attached to these typical translational gripper to replace the common monolithic jaws and provide the gripper with shape-adaptation capabilities without any control or sensors. A new design is introduced here and specially optimized for collaborative robots. The kinetostatic analysis of this new design is first discussed and then followed by the optimization of relevant geometric parameters taking into account the specificities of collaborative robots. Finally, a practical prototype attached to a very common collaborative robot is demonstrated. While the resulting finger design could be attached to any translational gripper, specifically targeting collaborative robots as an application allows for more liberty in the choice of certain design parameters and more constraints for others

Intelligent Haptic Perception for Physical Robot Interaction

Doctorado en Ingeniería mecatrónica. Fecha de entrega de la Tesis doctoral: 8 de enero de 2020. Fecha de lectura de Tesis doctoral: 30 de marzo 2020.The dream of having robots living among us is coming true thanks to the recent advances in Artificial Intelligence (AI). The gap that still exists between that dream and reality will be filled by scientific research, but manifold challenges are yet to be addressed. Handling the complexity and uncertainty of real-world scenarios is still the major challenge in robotics nowadays. In this respect, novel AI methods are giving the robots the capability to learn from experience and therefore to cope with real-life situations. Moreover, we live in a physical world in which physical interactions are both vital and natural. Thus, those robots that are being developed to live among humans must perform tasks that require physical interactions. Haptic perception, conceived as the idea of feeling and processing tactile and kinesthetic sensations, is essential for making this physical interaction possible. This research is inspired by the dream of having robots among us, and therefore, addresses the challenge of developing robots with haptic perception capabilities that can operate in real-world scenarios. This PhD thesis tackles the problems related to physical robot interaction by employing machine learning techniques. Three AI solutions are proposed for different physical robot interaction challenges: i) Grasping and manipulation of humans’ limbs; ii) Tactile object recognition; iii) Control of Variable-Stiffness-Link (VSL) manipulators. The ideas behind this research work have potential robotic applications such as search and rescue, healthcare or rehabilitation. This dissertation consists of a compendium of publications comprising as the main body a compilation of previously published scientific articles. The baseline of this research is composed of a total of five papers published in prestigious peer-reviewed scientific journals and international robotics conferences

Grasp and stress analysis of an underactuated finger for proprioceptive tactile sensing

This paper presents the design and evaluation of a new sensorized underactuated self-adaptive finger. The design incorporates a two-degrees-of-freedom link-driven underactuated mechanism with an embedded load cell for contact force measurement and a trimmer potentiometer for acquiring joint variables. The utilization of proprioceptive (internal) sensors results in tactile-like sensations in the finger without compromising the size and complexity of the proposed design. To obtain an optimum finger design, the placement of the load cell is analyzed using finite element method. The design of the finger features a particular rounded shape of the distal phalanx and specific size ratio between the phalanxes to enable both precision and power grasps. A quantitative evaluation of the grasp efficiency by constructing a grasp wrench space is provided. The effectiveness of the proposed design is verified through experimental results that demonstrate the grasp external wrench tolerance, shape adaptability, and tactile capability. All CAD files and ROS package for the proposed underactuated design can be found on https://github.com/mahyaret

Actuators and sensors for application in agricultural robots: A review

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future

Soft Robotic Grippers

Advances in soft robotics, materials science, and stretchable electronics have enabled rapid progress in soft grippers. Here, a critical overview of soft robotic grippers is presented, covering different material sets, physical principles, and device architectures. Soft gripping can be categorized into three technologies, enabling grasping by: a) actuation, b) controlled stiffness, and c) controlled adhesion. A comprehensive review of each type is presented. Compared to rigid grippers, end-effectors fabricated from flexible and soft components can often grasp or manipulate a larger variety of objects. Such grippers are an example of morphological computation, where control complexity is greatly reduced by material softness and mechanical compliance. Advanced materials and soft components, in particular silicone elastomers, shape memory materials, and active polymers and gels, are increasingly investigated for the design of lighter, simpler, and more universal grippers, using the inherent functionality of the materials. Embedding stretchable distributed sensors in or on soft grippers greatly enhances the ways in which the grippers interact with objects. Challenges for soft grippers include miniaturization, robustness, speed, integration of sensing, and control. Improved materials, processing methods, and sensing play an important role in future research

Development of an automated robot vision component handling system

Thesis (M. Tech. (Engineering: Electrical)) -- Central University of technology, Free State, 2013In the industry, automation is used to optimize production, improve product quality and increase profitability. By properly implementing automation systems, the risk of injury to workers can be minimized. Robots are used in many low-level tasks to perform repetitive, undesirable or dangerous work. Robots can perform a task with higher precision and accuracy to lower errors and waste of material. Machine Vision makes use of cameras, lighting and software to do visual inspections that a human would normally do. Machine Vision is useful in application where repeatability, high speed and accuracy are important. This study concentrates on the development of a dedicated robot vision system to automatically place components exiting from a conveyor system onto Automatic Guided Vehicles (AGV). A personal computer (PC) controls the automated system. Software modules were developed to do image processing for the Machine Vision system as well as software to control a Cartesian robot. These modules were integrated to work in a real-time system. The vision system is used to determine the parts‟ position and orientation. The orientation data are used to rotate a gripper and the position data are used by the Cartesian robot to position the gripper over the part. Hardware for the control of the gripper, pneumatics and safety systems were developed. The automated system‟s hardware was integrated by the use of the different communication protocols, namely DeviceNet (Cartesian robot), RS-232 (gripper) and Firewire (camera)

Research and development of a rescue robot end-effector

Includes abstract.Includes bibliographical references.This report details the research, design, development and testing of an end-effector system for use on an Urban Search and Rescue (USAR) robot which is in development in the Robotics and Agents Research Laboratory (RARL) at the University of Cape Town (UCT). This is the 5th generation Mobile Robot Platform (MRP) that UCT has developed ... codenamed ‘Ratel’. USAR robots used to be mainly of the observation type, but new robots (including UCT’s Ratel MRP) are being developed to deal with inherently dynamic, complex and unpredictable disaster response situations, particularly related to object manipulation and gripping. In order to actively interact with the environment, a flexible and robust gripping system is vital. [an] end-effector solution ... was developed for the Ratel manipulator arm to fulfil these functions