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

Getting the Ball Rolling: Learning a Dexterous Policy for a Biomimetic Tendon-Driven Hand with Rolling Contact Joints

Biomimetic, dexterous robotic hands have the potential to replicate much of the tasks that a human can do, and to achieve status as a general manipulation platform. Recent advances in reinforcement learning (RL) frameworks have achieved remarkable performance in quadrupedal locomotion and dexterous manipulation tasks. Combined with GPU-based highly parallelized simulations capable of simulating thousands of robots in parallel, RL-based controllers have become more scalable and approachable. However, in order to bring RL-trained policies to the real world, we require training frameworks that output policies that can work with physical actuators and sensors as well as a hardware platform that can be manufactured with accessible materials yet is robust enough to run interactive policies. This work introduces the biomimetic tendon-driven Faive Hand and its system architecture, which uses tendon-driven rolling contact joints to achieve a 3D printable, robust high-DoF hand design. We model each element of the hand and integrate it into a GPU simulation environment to train a policy with RL, and achieve zero-shot transfer of a dexterous in-hand sphere rotation skill to the physical robot hand.Comment: for project website, see https://srl-ethz.github.io/get-ball-rolling/ . for video, see https://youtu.be/YahsMhqNU8o . Submitted to the 2023 IEEE-RAS International Conference on Humanoid Robot

Origami-inspired kinematic morphing surfaces

In the past decades, an emerging technology has tried to build robots from soft materials to mimic living organisms in nature. Despite the flexibility and adaptability offered by such robots, the soft materials introduce very high or even infinite degrees of freedom (DoFs). It is thus challenging to achieve controllable shape changes on soft materials, which are essential for robots to carry out their functions. Many material-based approaches have been attempted to constrain the excessive DoFs of soft materials, so that they can bend, stretch, or twist as desired. In most applications, considering that only limited mobility is required to perform certain tasks, it would also be feasible to employ mechanical coupling to remove unwanted motions. To achieve this, engineers resort to origami techniques to design predictable and controllable robotic structures. However, most origami-inspired robots are built from existing patterns, where the material thickness is always neglected. Using zero-thickness sheets restricts the modelling accuracy, fabrication flexibility, and motion possibility. A recent study reveals that considering material thickness can further reduce the overall DoFs of origami, since its mechanical model is often overconstrained and differs significantly from that of the zero-thickness one. The novel structures with thickness, known as thick-panel origami, were originally developed for space use and are not accessible to roboticists. Hence, a thorough investigation is needed to develop thick-panel origami targeting robotic applications. This thesis is thus centred on two aspects. The first is to systematically design thick-panel origami for shape-changing, namely morphing surfaces. The second part extends selected surfaces into the design of intelligent robots, with the aim of simplified design, actuation, and control. The main achievements of this research are as follows. Firstly, a systematic design methodology is proposed to map thick-panel origami with 6R spatial overconstrained linkages. A library of morphing units whose thicknesses are uniform and not negligible is thus uncovered. Morphing surfaces, which are the tessellations or assemblies of morphing units, are then demonstrated to achieve common soft material behaviours, including bending, expanding, and twisting. Complex motions such as wrapping and curling are also presented. The mobility of these surfaces is restricted to one, while bifurcations may exist for extra motion possibilities. Secondly, a robotic gripper is designed from the wrapping surface. By exploiting the bifurcation and compliance of the surface, the proposed gripper has achieved a balance between motion dexterity and control complexity, aiming to solve the control challenges of grasping and manipulation. More specifically, the gripper can grasp objects of various shapes with one motor and conduct manipulations with only two control inputs, as opposed to many current end effectors that can only grasp or need around 20 actuators for manipulation tasks. On top of this, the gripper can be 3D-printed with ease, largely streamlining the mechanical design and fabrication process. Lastly, a reconfigurable robot is demonstrated on the curling surface to mimic a millipede's morphology. The robot can not only morph into a coil but also reconfigure into wave-like and triangular shapes. The reconfigurability is achieved by utilising the kinematic bifurcations of the surface without increasing the system's overall DoF. The design is also free from module disconnection and reconnection for new configurations, making the system more robust. The proof-of-concept robotic study has showcased the potential of maintaining reconfigurability with a relatively straightforward control strategy

Adaptive Underactuated Finger with Active Rolling Surface

This paper presents the design, prototype and kinematic model of a new adaptive underactuated finger with an articulated skin/surface that is able to bend and, at the same time, provides active rolling motion along its central axis while keeping the finger configuration. The design is based on a planar chain of overlapping spherical phalanxes that are tendon-driven. The finger has an articulated surface made of an external chain of hollow universal joints that can rotate via its central axis on the surface of the internal structure. The outer surface provides a second active Degree of Freedom (DoF). The two actuators, driving the bending and/or rolling motion, can be used independently. A set of experiments have been included to validate and measure the performance of the prototype for the grasping and rolling actions. The proposed finger can be built with a different number of phalanxes and sizes. A number of these fingers can be arranged along a palm structure resulting in a multi-finger robotic grasper for applications that require adaptation and in-hand manipulation capabilities such as pHRI

Systematic object-invariant in-hand manipulation via reconfigurable underactuatuation: introducing the RUTH gripper

We introduce a reconfigurable underactuated robot hand able to perform systematic prehensile in-hand manipulations regardless of object size or shape. The hand utilises a two-degree-of-freedom five-bar linkage as the palm of the gripper, with three three-phalanx underactuated fingers—jointly controlled by a single actuator—connected to the mobile revolute joints of the palm. Three actuators are used in the robot hand system in total, one for controlling the force exerted on objects by the fingers through an underactuated tendon system, and two for changing the configuration of the palm and thus the positioning of the fingers. This novel layout allows decoupling grasping and manipulation, facilitating the planning and execution of in-hand manipulation operations. The reconfigurable palm provides the hand with a large grasping versatility, and allows easy computation of a map between task space and joint space for manipulation based on distance-based linkage kinematics. The motion of objects of different sizes and shapes from one pose to another is then straightforward and systematic, provided the objects are kept grasped.This is guaranteed independently and passively by the underactuated fingers using a custom tendon routing method, which allows no tendon length variation when the relative finger base positions change with palm reconfigurations. We analyse the theoretical grasping workspace and grasping and manipulation capability of the hand, present algorithms forcomputing the manipulation map and in-hand manipulation planning, and evaluate all these experimentally. Numericaland empirical results of several manipulation trajectories with objects of different size and shape clearly demonstrate the viability of the proposed concept

The RUTH Gripper: systematic object-invariant prehensile in-hand manipulation via reconfigurable underactuation

We introduce a reconfigurable underactuated robothand able to perform systematic prehensile in-hand manipu-lations regardless of object size or shape. The hand utilisesa two-degree-of-freedom five-bar linkage as the palm of thegripper, with three three-phalanx underactuated fingers—jointlycontrolled by a single actuator—connected to the mobile revolutejoints of the palm. Three actuators are used in the robot handsystem, one for controlling the force exerted on objects by thefingers and two for changing the configuration of the palm.This novel layout allows decoupling grasping and manipulation,facilitating the planning and execution of in-hand manipulationoperations. The reconfigurable palm provides the hand withlarge grasping versatility, and allows easy computation of amap between task space and joint space for manipulation basedon distance-based linkage kinematics. The motion of objects ofdifferent sizes and shapes from one pose to another is thenstraightforward and systematic, provided the objects are keptgrasped. This is guaranteed independently and passively by theunderactuated fingers using a custom tendon routing method,which allows no tendon length variation when the relative fingerbase position changes with palm reconfigurations. We analysethe theoretical grasping workspace and manipulation capabilityof the hand, present algorithms for computing the manipulationmap and in-hand manipulation planning, and evaluate all theseexperimentally. Numerical and empirical results of several ma-nipulation trajectories with objects of different size and shapeclearly demonstrate the viability of the proposed concept

Ball-and-finger system: modeling and optimal trajectories

A rigid-body model of a finger interacting with a trackball is considered. The proposed system is a suitable candidate for studying trajectory generation when interaction plays an important role, such as in assembly and manipulation tasks. The mathematical model consists of a ball with a spherical joint constraint, a finger with three degrees of freedom, and the Coulomb friction model. From first principles, we derive a hybrid, high-index differential-algebraic equation for modeling the system dynamics, which is used for both simulation and finding optimal trajectories. For this problem, task planning, path planning, and trajectory generation are strongly interrelated, which makes using an integrated approach to trajectory generation inevitable. Moreover, the trajectory generation algorithm has to handle a number of important features, e.g., unilateral and non-holonomic constraints