A Unified Multimodal Interface for the RELAX High-Payload Collaborative Robot.

This manuscript introduces a mobile cobot equipped with a custom-designed high payload arm called RELAX combined with a novel unified multimodal interface that facilitates Human-Robot Collaboration (HRC) tasks requiring high-level interaction forces on a real-world scale. The proposed multimodal framework is capable of combining physical interaction, Ultra Wide-Band (UWB) radio sensing, a Graphical User Interface (GUI), verbal control, and gesture interfaces, combining the benefits of all these different modalities and allowing humans to accurately and efficiently command the RELAX mobile cobot and collaborate with it. The effectiveness of the multimodal interface is evaluated in scenarios where the operator guides RELAX to reach designated locations in the environment while avoiding obstacles and performing high-payload transportation tasks, again in a collaborative fashion. The results demonstrate that a human co-worker can productively complete complex missions and command the RELAX mobile cobot using the proposed multimodal interaction framework.

Horse-like walking, trotting, and galloping derived from kinematic Motion Primitives (kMPs) and their application to walk/trot transitions in a compliant quadruped robot.

This manuscript proposes a method to directly transfer the features of horse walking, trotting, and galloping to a quadruped robot, with the aim of creating a much more natural (horse-like) locomotion profile. A principal component analysis on horse joint trajectories shows that walk, trot, and gallop can be described by a set of four kinematic Motion Primitives (kMPs). These kMPs are used to generate valid, stable gaits that are tested on a compliant quadruped robot. Tests on the effects of gait frequency scaling as follows: results indicate a speed optimal walking frequency around 3.4 Hz, and an optimal trotting frequency around 4 Hz. Following, a criterion to synthesize gait transitions is proposed, and the walk/trot transitions are successfully tested on the robot. The performance of the robot when the transitions are scaled in frequency is evaluated by means of roll and pitch angle phase plots.

XBot2D: towards a robotics hybrid cloud architecture for field robotics.

Nowadays, robotics applications requiring the execution of complex tasks in real-world scenarios are still facing many challenges related to highly unstructured and dynamic environments in domains such as emergency response and search and rescue where robots have to operate for prolonged periods trading off computational performance with increased power autonomy and vice versa. In particular, there is a crucial need for robots capable of adapting to such settings while at the same time providing robustness and extended power autonomy. A possible approach to overcome the conflicting demand of a computational performing system with the need for long power autonomy is represented by cloud robotics, which can boost the computational capabilities of the robot while reducing the energy consumption by exploiting the offload of resources to the cloud. Nevertheless, the communication constraint due to limited bandwidth, latency, and connectivity, typical of field robotics, makes cloud-enabled robotics solutions challenging to deploy in real-world applications. In this context, we designed and realized the XBot2D software architecture, which provides a hybrid cloud manager capable of dynamically and seamlessly allocating robotics skills to perform a distributed computation based on the current network condition and the required latency, and computational/energy resources of the robot in use. The proposed framework leverage on the two dimensions, i.e., 2D (local and cloud), in a transparent way for the user, providing support for Real-Time (RT) skills execution on the local robot, as well as machine learning and A.I. resources on the cloud with the possibility to automatically relocate the above based on the required performances and communication quality. XBot2D implementation and its functionalities are presented and validated in realistic tasks involving the CENTAURO robot and the Amazon Web Service Elastic Computing Cloud (AWS EC2) infrastructure with different network conditions.

A Haptic Shared Autonomy With Partial Orientation Regulation for DoF Deficiency in Remote Side.

Orientation regulation permits an autonomous controller to regulate the operators' orientation commands automatically. Although kinds of orientation regulation strategies have been proposed for various purposes, few works have focused on the partial orientation regulation (POR), which requires an autonomous controller to prevent the unreachable rotational motion for safety, while preserving the remaining motions for intuitiveness. However, the POR is deeply demanded for systems with Degree-of-Freedom (DoF) deficiency in remote side. The POR is a more challenging task owing to: First, it is difficult to decompose an orientation into reachable and unreachable components due to the non-linear structure of the rotation group SO(3). Second, it is non-trivial to design a haptic rendering algorithm which can indicate the missing DoF information to human operators. To address the rotational DoF deficiency, we propose a haptic shared autonomy with POR ability, based on the perpendicular curve theory in SO(3). The proposed method can partially regulate the operator's orientation command to discard the unreachable motions and preserve the remaining motions for follower robots. Here the conventional "master" and "slave" are all replaced by "leader" and "follower" to avoid the concern of association to racism and human subjugation. In addition, a haptic rendering algorithm is designed to display correct haptic cues about the missing DoF to operators. The simulation and experimental results validate the effectiveness of the proposed method.

Horizon: A Trajectory Optimization Framework for Robotic Systems.

This paper presents Horizon, an open-source framework for trajectory optimization tailored to robotic systems that implements a set of tools to simplify the process of dynamic motion generation. Its user-friendly Python-based API allows designing the most complex robot motions using a simple and intuitive syntax. At the same time, the modular structure of Horizon allows for easy customization on many levels, providing several recipes to handle fixed and floating-base systems, contact switching, variable time nodes, multiple transcriptions, integrators and solvers to guarantee flexibility towards diverse tasks. The proposed framework relies on direct simultaneous methods to transcribe the optimal problem into a nonlinear programming problem that can be solved by state-of-the-art solvers. In particular, it provides several off-the-shelf solvers, as well as two custom-implemented solvers, i.e. GN-SQP and Iterative Linear-Quadratic Regulator. Solutions of optimized problems can be stored for warm-starting, and re-sampled at a different frequency while enforcing dynamic feasibility. The proposed framework is validated through a number of use-case scenarios involving several robotic platforms. Finally, an in-depth analysis of a specific case study is carried out, where a highly dynamic motion (i.e., a twisting jump using the quadruped robot Spot® from BostonDynamics) is generated, in order to highlight the main features of the framework and demonstrate its capabilities.

Variable stiffness locomotion with guaranteed stability for quadruped robots traversing uneven terrains.

Quadruped robots are widely applied in real-world environments where they have to face the challenges of walking on unknown rough terrains. This paper presents a control pipeline that generates robust and compliant legged locomotion for torque-controlled quadruped robots on uneven terrains. The Cartesian motion planner is designed to be reactive to unexpected early and late contacts using the estimated contact forces. Moreover, we present a novel scheme of optimal stiffness modulation that aims to coordinate desired compliance and tracking performance. It optimizes joint stiffness and contact forces coordinately in a quadratic programming (QP) formulation, where the constraints of non-slipping contacts and torque limits are imposed as well. In addition, the issue of stability under variable stiffness control is solved by imposing a tank-based passivity constraint explicitly. We finally validate the proposed control pipeline on our quadruped robot CENTAURO in experiments on uneven terrains and, through comparative tests, demonstrate the improvements of the variable stiffness locomotion.

Omnidirectional Walking Pattern Generator Combining Virtual Constraints and Preview Control for Humanoid Robots.

This paper presents a novel omnidirectional walking pattern generator for bipedal locomotion combining two structurally different approaches based on the virtual constraints and the preview control theories to generate a flexible gait that can be modified on-line. The proposed strategy synchronizes the displacement of the robot along the two planes of walking: the zero moment point based preview control is responsible for the lateral component of the gait, while the sagittal motion is generated by a more dynamical approach based on virtual constraints. The resulting algorithm is characterized by a low computational complexity and high flexibility, requisite for a successful deployment to humanoid robots operating in real world scenarios. This solution is motivated by observations in biomechanics showing how during a nominal gait the dynamic motion of the human walk is mainly generated along the sagittal plane. We describe the implementation of the algorithm and we detail the strategy chosen to enable omnidirectionality and on-line gait tuning. Finally, we validate our strategy through simulation experiments using the COMAN + platform, an adult size humanoid robot developed at Istituto Italiano di Tecnologia. Finally, the hybrid walking pattern generator is implemented on real hardware, demonstrating promising results: the WPG trajectories results in open-loop stable walking in the absence of external disturbances.

NSPG: An Efficient Posture Generator Based on Null-Space Alteration and Kinetostatics Constraints.

Most of the locomotion and contact planners for multi-limbed robots rely on a reduction of the search space to improve the performance of their algorithm. Posture generation plays a fundamental role in these types of planners providing a collision-free, statically stable whole-body posture, projected onto the planned contacts. However, posture generation becomes particularly tedious for complex robots moving in cluttered environments, in which feasibility can be hard to accomplish. In this work, we take advantage of the kinematic structure of a multi-limbed robot to present a posture generator based on hierarchical inverse kinematics and contact force optimization, called the null-space posture generator (NSPG), able to efficiently satisfy the aforementioned requisites in short times. A new configuration of the robot is produced through conservatively altering a given nominal posture exploiting the null-space of the contact manifold, satisfying geometrical and kinetostatics constraints. This is achieved through an adaptive random velocity vector generator that lets the robot explore its workspace. To prove the validity and generality of the proposed method, simulations in multiple scenarios are reported employing different robots: a wheeled-legged quadruped and a biped. Specifically, it is shown that the NSPG is particularly suited in complex cluttered scenarios, in which linear collision avoidance and stability constraints may be inefficient due to the high computational cost. In particular, we show an improvement of performances being our method able to generate twice feasible configurations in the same period. A comparison with previous methods has been carried out collecting the obtained results which highlight the benefits of the NSPG. Finally, experiments with the CENTAURO platform, developed at Istituto Italiano di Tecnologia, are carried out showing the applicability of the proposed method to a real corridor scenario.

A Simple Yet Effective Whole-Body Locomotion Framework for Quadruped Robots.

In the context of legged robotics, many criteria based on the control of the Center of Mass (CoM) have been developed to ensure a stable and safe robot locomotion. Defining a whole-body framework with the control of the CoM requires a planning strategy, often based on a specific type of gait and a reliable state-estimation. In a whole-body control approach, if the CoM task is not specified, the consequent redundancy can still be resolved by specifying a postural task that set references for all the joints. Therefore, the postural task can be exploited to keep a well-behaved, stable kinematic configuration. In this work, we propose a generic locomotion framework which is able to generate different kind of gaits, ranging from very dynamic gaits, such as the trot, to more static gaits like the crawl, without the need to plan the CoM trajectory. Consequently, the whole-body controller becomes planner-free and it does not require the estimation of the floating base state, which is often prone to drift. The framework is composed of a priority-based whole-body controller that works in synergy with a walking pattern generator. We show the effectiveness of the framework by presenting simulations on different types of simulated terrains, including rough terrain, using different quadruped platforms.

An Overview on Principles for Energy Efficient Robot Locomotion.

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms. The covered different perspectives include actuation, leg structure, control and locomotion principles. We review various robotic actuators exploiting compliance in series and in parallel with the drive-train to permit energy recycling during locomotion. We discuss the importance of limb segmentation under efficiency aspects and with respect to design, dynamics analysis and control of legged robots. This paper also reviews a number of control approaches allowing for energy efficient locomotion of robots by exploiting the natural dynamics of the system, and by utilizing optimal control approaches targeting locomotion expenditure. To this end, a set of locomotion principles elaborating on models for energetics, dynamics, and of the systems is studied.

Enteral nutrition affects nitric oxide production in peripheral blood and liver after a postoperative lipopolysaccharide-induced endotoxemia in rats.

OBJECTIVES: Sepsis is a common complication in the early postoperative period, leading to the augmentation of oxidative and nitrosative stresses. The present study investigated the role of enteral nutrition on nitric oxide (NO) production after a lipopolysaccharide (LPS)-induced endotoxemia as an index of nitrosative stress. METHODS: Fifty rats were subjected to midline laparotomy and feeding gastrostomy. Ten rats served as controls after recovering from operative stress. The remaining rats received, through gastrostomy, enteral nutrition or placebo feeding for 24 h, after which they were injected intraperitoneally with LPS or equal volume of saline. Two hours later blood and liver tissue were collected. NO production was quantified in serum samples and homogenates of liver tissue by a modification of Griess's reaction. NO synthase (NOS) mRNA expression was examined in homogenate of liver tissue by reverse transcription-polymerase chain reaction. RESULTS: The operation significantly increased basal NO production in rat serum. LPS induced a further significant increase of NO levels. Enteral feeding of rats significantly decreased NO levels in both groups. In contrast, enteral nutrition was found to increase significantly NO levels in liver homogenates from rats treated with LPS. A constitutive endothelial NOS mRNA expression was found in liver tissue, whereas LPS administration induced inducible NOS mRNA expression in liver tissue regardless of enteral feeding. CONCLUSION: These findings indicate that early enteral feeding leads to a reduction in circulating NO levels induced by operation and endotoxemia, but increases hepatic NO levels in endotoxemia probably by the effect of LPS-induced inducible NOS on the increased L-arginine uptake.

A Human-Robot Co-Manipulation Approach Based on Human Sensorimotor Information.

This paper aims to improve the interaction and coordination between the human and the robot in cooperative execution of complex, powerful, and dynamic tasks. We propose a novel approach that integrates online information about the human motor function and manipulability properties into the hybrid controller of the assistive robot. Through this human-in-the-loop framework, the robot can adapt to the human motor behavior and provide the appropriate assistive response in different phases of the cooperative task. We experimentally evaluate the proposed approach in two human-robot co-manipulation tasks that require specific complementary behavior from the two agents. Results suggest that the proposed technique, which relies on a minimum degree of task-level pre-programming, can achieve an enhanced physical human-robot interaction performance and deliver appropriate level of assistance to the human operator.

A real-time and reduced-complexity approach to the detection and monitoring of static joint overloading in humans.

This paper proposes a novel technique for the real-time estimation of the joint torques variations in humans while performing heavy manipulation tasks. To achieve this, the method is based on the deviations of the Centre of Pressure (CoP) and Ground Reaction Force (GRF) in the presence of interaction forces. The CoP and GRF variations are calculated from the difference between the estimated values (assuming no interaction forces) using a pre-identified statically equivalent serial chain (SESC) and the measured ones (with the effect of interaction forces) using an external device. The calculated variation vectors and the measured joint angles of the human body are then used for the estimation of the overloading joint torques in real-time. We evaluated the efficacy of the proposed method both in simulations and experiments, in various poses of the human and interaction force profiles.

A novel human effort estimation method for knee assistive exoskeletons.

In this work we present a novel method to estimate online the torques at the knee joints with the goal to generate reference signals for knee assistive devices. One of the main advantages of the proposed approach is its reduced sensing requirements, which leads to an ergonomic setup with minimal instrumentation, especially above the knee and of the upper body. Indeed, only the measurement of the forces and torques exchanged between the ground and the user's feet, the posture of the shanks, and the model of the user's shank itself are needed for the estimation of the knee torque. The method does not require information of the state of the upper body and of a possible payload i.e. body pose, mass and center of mass (CoM) location. As a result, a minimalistic sensory system consisting of sensorized shoes and IMUs to track the shanks' orientation are adequate, allowing for an easily wearable and portable setup. The estimation of the knee torques is achieved by imposing an equilibrium condition to the user's shank. Several experiments were performed to test the effectiveness of the proposed estimation method under different body postures and motions (e.g. squat motion and switching foot contacts) and payloads (e.g. by holding weights at different arm postures resulting in variable upper body CoM). Finally an assistive task, conducted with the iT-Knee bipedal system is presented, where the lifted payload changed its CoM location over time.

Synergy-Based Bilateral Port: A Universal Control Module for Tele-Manipulation Frameworks Using Asymmetric Master-Slave Systems.

Endowing tele-manipulation frameworks with the capability to accommodate a variety of robotic hands is key to achieving high performances through permitting to flexibly interchange the end-effector according to the task considered. This requires the development of control policies that not only cope with asymmetric master-slave systems but also whose high-level components are designed in a unified space in abstraction from the devices specifics. To address this dual challenge, a novel synergy port is developed that resolves the kinematic, sensing, and actuation asymmetries of the considered system through generating motion and force feedback references in the hardware-independent hand postural synergy space. It builds upon the concept of the Cartesian-based synergy matrix, which is introduced as a tool mapping the fingertips Cartesian space to the directions oriented along the grasp principal components. To assess the effectiveness of the proposed approach, the synergy port has been integrated into the control system of a highly asymmetric tele-manipulation framework, in which the 3-finger hand exoskeleton HEXOTRAC is used as a master device to control the SoftHand, a robotic hand whose transmission system relies on a single motor to drive all joints along a soft synergistic path. The platform is further enriched with the vision-based motion capture system Optitrack to monitor the 6D trajectory of the user's wrist, which is used to control the robotic arm on which the SoftHand is mounted. Experiments have been conducted with the humanoid robot COMAN and the KUKA LWR robotic manipulator. Results indicate that this bilateral interface is highly intuitive and allows users with no prior experience to reach, grasp, and transport a variety of objects exhibiting very different shapes and impedances. In addition, the hardware and control solutions proved capable of accommodating users with different hand kinematics. Finally, the proposed control framework offers a universal, flexible, and intuitive interface allowing for the performance of effective tele-manipulations.

Exploring teleimpedance and tactile feedback for intuitive control of the Pisa/IIT SoftHand.

This paper proposes a teleimpedance controller with tactile feedback for more intuitive control of the Pisa/IIT SoftHand. With the aim to realize a robust, efficient and low-cost hand prosthesis design, the SoftHand is developed based on the motor control principle of synergies, through which the immense complexity of the hand is simplified into distinct motor patterns. Due to the built-in flexibility of the hand joints, as the SoftHand grasps, it follows a synergistic path while allowing grasping of objects of various shapes using only a single motor. The DC motor of the hand incorporates a novel teleimpedance control in which the user's postural and stiffness synergy references are tracked in real-time. In addition, for intuitive control of the hand, two tactile interfaces are developed. The first interface (mechanotactile) exploits a disturbance observer which estimates the interaction forces in contact with the grasped object. Estimated interaction forces are then converted and applied to the upper arm of the user via a custom made pressure cuff. The second interface employs vibrotactile feedback based on surface irregularities and acceleration signals and is used to provide the user with information about the surface properties of the object as well as detection of object slippage while grasping. Grasp robustness and intuitiveness of hand control were evaluated in two sets of experiments. Results suggest that incorporating the aforementioned haptic feedback strategies, together with user-driven compliance of the hand, facilitate execution of safe and stable grasps, while suggesting that a low-cost, robust hand employing hardware-based synergies might be a good alternative to traditional myoelectric prostheses.

On the Kinematic Motion Primitives (kMPs) - Theory and Application.

Human neuromotor capabilities guarantee a wide variety of motions. A full understanding of human motion can be beneficial for rehabilitation or performance enhancement purposes, or for its reproduction on artificial systems like robots. This work aims at describing the complexity of human motion in a reduced dimensionality, by means of kinematic Motion Primitives (kMPs). A set of five invariant kMPs are identified for periodic motions, and a set of two kMPs for discrete motions. It is shown how these two sets of kMPs can be combined to synthesize more complex motion as the simultaneous execution of the periodic and the discrete motions. The results reported are an evidence of the theory of Central Pattern Generators (CPG), showing its effects on the kinematics, and are related to what presented in the literature on the Motor Primitives extracted from EMG signals. Experimental tests with the COmpliant huMANoid (COMAN) were performed to show that the kMPs extracted from human subjects can be used to transfer the features of human locomotion to the gait of a robot.

Feeling through Tactile Displays: A Study on the Effect of the Array Density and Size on the Discrimination of Tactile Patterns.

Tactile arrays are devices that can provide spatially distributed cutaneous signals delivering crucial information during virtual haptic exploration or remote manipulation procedures. Two of the key specifications of a tactile array are the tactor spacing and array size that are believed to directly affect the device performance. In most of the systems developed so far, these two parameters have been chosen by trial and error or by trying to match the tactor density to the spatial resolution in the human fingertip. The objective of this work is to study the effect of tactor spacing and array size on the tactile arrays performance by measuring human tactile discrimination ability. Psychophysical experiments were performed to obtain the differential threshold for discrimination of a ridge angle and the shape recognition performance while exploring edge-based patterns. The patterns were explored through different passive (nonactuated) tactile arrays of vertically moving pins and also directly with the finger. Results indicate that a tactile array of 1.8 mm tactor spacing and 1 cm(2) array size transmits the pattern information with a good level of accuracy. This work shows that tactile devices with low complexity (small number of tactors) are still effective in conveying tactile cues. Moreover, this work provides performance measures that determinate the capabilities of tactile pin arrays to convey accurately tactile information.

A multi-DOF robotic exoskeleton interface for hand motion assistance.

This paper outlines the design and development of a robotic exoskeleton based rehabilitation system. A portable direct-driven optimized hand exoskeleton system has been proposed. The optimization procedure primarily based on matching the exoskeleton and finger workspaces guided the system design. The selection of actuators for the proposed system has emerged as a result of experiments with users of different hand sizes. Using commercial sensors, various hand parameters, e.g. maximum and average force levels have been measured. The results of these experiments have been mapped directly to the mechanical design of the system. An under-actuated optimum mechanism has been analysed followed by the design and realization of the first prototype. The system provides both position and force feedback sensory information which can improve the outcomes of a professional rehabilitation exercise.