Robotics

In a telerehabilitation environment, it is difficult for a therapist to understand the condition of a patient’s finger joints because of the lack of direct assessment. In particular, not enabling the provision of spasticity evaluation significantly reduces the optimal performance of telerehabilitation. In a previous study, it has been proposed that finger stiffness could be estimated using an analytical model of a whole-finger soft actuator. However, because the whole-finger soft actuators require high air pressure for high bending performance and are costly to customize for each patient, using joint modular soft actuators for telerehabilitation turns to be a necessity, though stiffness estimation with joint modular soft actuators has not been studied yet. Another problem is caused by using a marker-based joint angle measurement, which requires the markers to be attached to the exact positions, and limits its application in telerehabilitation. In this study, we proposed a procedure of finger joint stiffness estimation that combines information acquired from a joint modular soft actuator and a marker-less hand joint position acquisition device. Correction parameters were added to the previous analytical model for -the bending analysis of a joint assisted using a joint modular soft actuator. Moreover, a multi-variate regression model was implemented for correcting joint angles obtained from the hand joint position acquisition device. As a result, a reasonable accuracy of stiffness estimation was achieved for rehabilitation with the joint modular soft actuators, which suggests the possibility of using the proposed method to evaluate the finger spasticity in a telerehabilitation environment. This is a big step forward towards optimal hand telerehabilitation. Full article

In recent years, many studies have shown that soft robots with elastic actuators enable robust interaction with the environment. Compliant joints can protect mechanical systems and provide better dynamic performance, thus offering huge potential for further developments of humanoid robots. This paper proposes a new biped robot. The new robot combines a torque sensor-based active elastic hip and a spring-based passive elastic knee/ankle. In the first part, the mechanical design is introduced, and in the second part, the kinematics and dynamics capabilities are described. Furthermore, we introduce a new extended capture-point-based walking pattern generator that calculates footstep positions, which are used as input for the controller of our new biped robot. The main contribution of this article is the novel mechanical design and an extended walking pattern generator. The new design offers a unique solution for cable-driven bipeds to achieve both balancing and walking. Meanwhile, the new walking pattern generator can generate smooth desired curves, which is an improvement over traditional generators that use a constant zero-moment-point (ZMP). A simple cartesian controller is applied to test the performance of the walking pattern generator. Although the robot has been built, all experiments regarding the pattern generator are still simulated using MATLAB/Simulink. The focus of this work is to analyze the mechanical design and show the capabilities of the robot by applying a new pattern generator. Full article

Obstacle avoidance is a challenging task in robot navigation, as it requires efficient and reliable methods to avoid collision and reach the desired goal. Artificial potential field methods are widely used for this purpose, as they are efficient, effective, and easy to implement. However, they are limited by the use of only one global attractor at the goal. This paper introduces and evaluates experimentally a novel technique that enhances the artificial potential field method with local attractors. Local attractors can be positioned around the obstacle so as to guide the robot detouring through preferred regions. Thus, the side the robot will pass by can be determined in advance, making the collision-free path predictable. The technique is formulated by modelling local attractors as optimal inflections, i.e., regions that do not show local minima, which coexist with the potential field generated by the obstacle and the global attractor. The method is validated using a laboratory setup that employs a camera and markers to track the poses of the robot, the obstacle, and the target. A series of experiments are conducted to examine the effect of the local attractor under different test conditions, obtained by varying the obstacle pose, the attraction intensity, and the robot velocity. The experimental results demonstrate the effectiveness of the proposed technique and highlight the aspects that require further investigation for its improvement and application. Full article

Compliance actuation systems are efficient and safe, drawing attention to their development. However, compliance has caused bandwidth loss, instability, and mechanical vibration in robotic systems. Variable physical damping was introduced to address these issues. This paper presents a technique for obtaining variable damping properties using an electromagnetic brake. The relationship mapping of the voltage and the braking torque is studied and applied to the variable damping concept. A new model is proposed to demonstrate the actuation system performance gained by introducing physical damping. The experimental setup comprises an electromagnetic brake and a motor with an integrated controller for speed control and torque feedback. The motor provides the motion, while the electromagnetic brake replicates the damping through a friction mechanism. The variable damping concept was evaluated experimentally using a 1-degree-of-freedom rotational system. Experimental results show that the proposed concept can generate the desired mechanical damping with a high degree of fidelity. Full article

This study provides a structured literature review of the recent COllaborative roBOT (COBOT) applications in industrial and service contexts. Several papers and research studies were selected and analyzed, observing the collaborative robot interactions, the control technologies and the market impact. This review focuses on stationary COBOTs that may guarantee flexible applications, resource efficiency, and worker safety from a fixed location. COBOTs offer new opportunities to develop and integrate control techniques, environmental recognition of time-variant object location, and user-friendly programming to interact safely with humans. Artificial Intelligence (AI) and machine learning systems enable and boost the COBOT’s ability to perceive its surroundings. A deep analysis of different applications of COBOTs and their properties, from industrial assembly, material handling, service personal assistance, security and inspection, Medicare, and supernumerary tasks, was carried out. Among the observations, the analysis outlined the importance and the dependencies of the control interfaces, the intention recognition, the programming techniques, and virtual reality solutions. A market analysis of 195 models was developed, focusing on the physical characteristics and key features to demonstrate the relevance and growing interest in this field, highlighting the potential of COBOT adoption based on (i) degrees of freedom, (ii) reach and payload, (iii) accuracy, and (iv) energy consumption vs. tool center point velocity. Finally, a discussion on the advantages and limits is summarized, considering anthropomorphic robot applications for further investigations. Full article

This paper presents results coming from a non-linear model predictive controller used to generate optimized trajectories specifically for an omnidirectional robot equipped with a spraying unit to mark on the floor the perimeter of dangerous areas or to move large palletized goods inside warehouses. Results on different trajectories and with moving obstacles are provided along with considerations on the controller performance. Full article

Prototyping and validating hardware–software components, sub-systems and systems within the intelligent transportation system-of-systems framework requires a modular yet flexible and open-access ecosystem. This work presents our attempt to develop such a comprehensive research and education ecosystem, called AutoDRIVE, for synergistically prototyping, simulating and deploying cyber-physical solutions pertaining to autonomous driving as well as smart city management. AutoDRIVE features both software as well as hardware-in-the-loop testing interfaces with openly accessible scaled vehicle and infrastructure components. The ecosystem is compatible with a variety of development frameworks, and supports both single- and multi-agent paradigms through local as well as distributed computing. Most critically, AutoDRIVE is intended to be modularly expandable to explore emergent technologies, and this work highlights various complementary features and capabilities of the proposed ecosystem by demonstrating four such deployment use-cases: (i) autonomous parking using probabilistic robotics approach for mapping, localization, path-planning and control; (ii) behavioral cloning using computer vision and deep imitation learning; (iii) intersection traversal using vehicle-to-vehicle communication and deep reinforcement learning; and (iv) smart city management using vehicle-to-infrastructure communication and internet-of-things. Full article

In this paper, we suggest an implementation of non-commutative logic and apply its operators for decision-making in a group of autonomous agents. The suggested operators extend the uninorm and absorbing norm aggregators and use an additional asymmetry parameter that defines the “level of non-commutativity”. The value of this parameter is specified using the perception bias of humans measured in the experiments. The suggested operators and decision-making method are illustrated by the simulated behavior of mobile robots in the group, which verified the possibility of processing systematic sensing errors, as well as of distinguishing and mimicking the biased decisions. Full article

The paper presents the design and experimental study of a synthesis method based on reference signal generation systems. The method can be used for all actuators of redundant manipulators. The aforementioned systems aim to save the dynamic control accuracy of the working tools of serial manipulators when they move along arbitrary spatial trajectories, taking into account restrictions in all degrees of freedom and special cases of their link positions. The maintenance of the control accuracy could be ensured by eliminating the reach of all degrees of freedom of manipulators to their limits and to indicated special positions, characterized by an ambiguity when solving the inverse kinematic problems of various serial manipulators. This is in addition to preventing the reach of their working tools to the boundaries of the working area due to the use of a redundant degree of freedom when approaching the indicated undesirable positions. The experimental studies performed in this paper confirm the efficiency of the proposed method and allow accurate characteristics to be obtained. Full article

Stair climbing is one of the most challenging tasks for vehicles, especially when transporting people and heavy loads. Although many solutions have been proposed and demonstrated in practice, it is necessary to further improve their climbing ability and safety. This paper presents a systematic review of the scientific and engineering stair climbing literature, providing brief descriptions of the mechanism and method of operation and highlighting the advantages and disadvantages of different types of climbing platform. To quantitatively evaluate the system performance, various metrics are presented that consider allowable payload, maximum climbing speed, maximum crossable slope, transport ability and their combinations. Using these metrics, it is possible to compare vehicles with different locomotion modes and properties, allowing researchers and practitioners to gain in-depth knowledge of stair-climbing vehicles and choose the best category for transporting people and heavy loads up a flight of stairs. Full article

Flexible manipulator systems in specific applications such as space exploration, nuclear waste treatment, medical applications, etc., often have characteristics superior to conventional rigid manipulator systems. However, their elasticity and complex dynamics lead to difficulties encountered in control processes. Research on improving the structure of the control model plays a very important role in reducing the above limitations and achieving great benefits for the flexible manipulator system. In this study, a general method for modelling a flexible robotic manipulator is introduced. Furthermore, two control models for flexible manipulators are proposed. The first model uses two proportional–integral–derivative (PID) controllers, where the first one is used for position control, and the other is applied for vibration reduction. The second model is an enhanced development of the first with the addition of a fuzzy logic controller to optimise oscillation suppression. Selected experimental results are presented and compared to evaluate the performance of the proposed control mechanisms. Full article

Human handwriting is an everyday task performed regularly by most people. In the domain of robotic painting, multiple calligraphy machines exist which were built to replicate some aspects of human artistic writing; however, most projects are limited to a specific style of handwriting, often Chinese calligraphy. We propose a two-stage pipeline that allows industrial robots to write text in arbitrary typefaces and scripts using paintbrushes. In the first stage, we extract a set of strokes from character glyphs which are similar to how humans choose strokes during writing. In the second stage, we generate corresponding brush trajectories by applying a brush model to the extracted strokes. Our brush model computes the required brush pressure to achieve the given stroke width while also accounting for brush lag. We also present a method to automatically measure the parameters needed to predict brush lag by painting and recording calibration patterns. Our method generates trajectories for text in any given typeface, which, when executed by a robotic arm, results in legible written text. We can render most writing systems, excluding emoji and ligatures, in which arbitrary texts can be specified to write. Full article

Digital models of industrial and collaborative manipulators are widely used for several applications, such as power-efficient trajectory definition, human–robot cooperation safety improvement, and prognostics and health management (PHM) algorithm development. Currently, models with simplified joints present in the literature have been used to evaluate robot macroscopic behavior. However, they are not suitable for the in-depth analyses required by those activities, such as PHM, which demand a punctual description of each subcomponent. This paper aims to fill this gap by presenting a high-fidelity multibody model of a UR5 collaborative robot, containing an accurate description of its full dynamics, electric motors, and gearboxes. Harmonic reducers were described through a translational equivalent lumped parameter model, allowing each constitutive element of the reducer to have its decoupled dynamics and mating forces through non-linear penalty contact models. To conclude, both the mathematical model and the real robot on a test rig were tested with a set of different trajectories. The experimental results highlight the ability of the proposed model to accurately replicate joint angular rotation, speed and torques in a wide range of operational scenarios. This research provides the basis for the development of a model-based PHM-oriented framework to carry out detailed and advanced analyses on the effects of manipulator degradations. Full article

This paper addresses the problem of building an occupancy grid map of an unknown environment using a swarm comprising resource-constrained robots, i.e., robots with limited exteroceptive and inter-robot sensing capabilities. Past approaches have, commonly, used random-motion models to disperse the swarm and explore the environment randomly, which do not necessarily consider prior information already contained in the map. Herein, we present a collaborative, effective exploration strategy that directs the swarm toward ‘promising’ frontiers by dividing the swarm into two teams: landmark robots and mapper robots, respectively. The former direct the latter, toward promising frontiers, to collect proximity measurements to be incorporated into the map. The positions of the landmark robots are optimized to maximize new information added to the map while also adhering to connectivity constraints. The proposed strategy is novel as it decouples the problem of directing the resource-constrained swarm from the problem of mapping to build an occupancy grid map. The performance of the proposed strategy was validated through extensive simulated experiments. Full article

Paraconsistent Annotated Logic (PAL) is a type of non-classical logic based on concepts that allow, under certain conditions, for one to accept contradictions without invalidating conclusions. The Paraconsistent Artificial Neural Cell of Learning (lPANCell) algorithm was created from PAL-based equations. With its procedures for learning discrete patterns being represented by values contained in the closed interval between 0 and 1, the lPANCell algorithm presents responses similar to those of nonlinear dynamical systems. In this work, several tests were carried out to validate the operation of the lPANCell algorithm in a learning from demonstration (LfD) framework applied to a linear Cartesian robot (gantry robot), which was moving rectangular metallic workpieces. For the LfD process used in the teaching of trajectories in the x and y axes of the linear Cartesian robot, a Paraconsistent Artificial Neural Network (lPANnet) was built, which was composed of eight lPANCells. The results showed that lPANnet has dynamic properties with a robustness to disturbances, both in the learning process by demonstration, as well as in the imitation process. Based on this work, paraconsistent artificial neural networks of a greater complexity, which are composed of lPANCells, can be formed. This study will provide a strong contribution to research regarding learning from demonstration frameworks being applied in robotics. Full article

Robots can be equipped with a range of senses to allow them to perceive and interact with the world in a more natural and intuitive way. These senses can include vision, hearing, touch, smell, and taste. Vision allows the robot to see and recognize objects and navigate its environment. Hearing enables the robot to recognize sounds and respond to vocal commands. Touch allows the robot to perceive information about the texture, shape, and temperature of objects through the sense of touch. Smell enables the robot to recognize and classify different odors. Taste enables the robot to identify the chemical composition of materials. The specific senses used in a robot will depend on the needs of the application, and many robots use a combination of different senses to perceive and interact with the environment. This paper reviews the five senses used in robots, their types, how they work, and other related information, while also discussing the possibility of a Sixth Sense. Full article

In this paper, the locomotion and steering control of a simulated Mini Cheetah quadruped robot was investigated in the presence of terrain characterised by low friction. Low-level locomotion and steering control were implemented via a central pattern generator approach, whereas high-level steering control manoeuvres were implemented by comparing a neural network and a linear model predictive controller in a dynamic simulation environment. A data-driven approach was adopted to identify the robot model using both a linear transfer function and a shallow artificial neural network. The results demonstrate that, whereas the linear approach showed good performance in high-friction terrain, in the presence of slippery conditions, the application of a neural network predictive controller improved trajectory accuracy and preserved robot safety with different steering manoeuvres. A comparative analysis was carried out using several performance indices. Full article

Accurate interaction force estimation can play an important role in optimizing human–robot interaction in an exoskeleton. In this work, we propose a novel approach for the system identification of exoskeleton dynamics in the presence of interaction forces as a whole multibody system without imposing any constraints on the exoskeleton dynamics. We hung the exoskeleton through a linear spring and excited the exoskeleton joints with chirp commands while measuring the exoskeleton–environment interaction force. Several structures of neural networks were trained to model the exoskeleton passive dynamics and estimate the interaction force. Our testing results indicated that a deep neural network with 250 neurons and 10 time–delays could obtain a sufficiently accurate estimation of the interaction force, resulting in an RMSE of 1.23 on Z–normalized applied torques and an adjusted $R^2$ of 0.89. Full article

This paper presents robot localization using building architectural plans and hierarchical SLAM. We extract geometric, semantic as well as topological information from the architectural plans in the form of walls and rooms, and create the topological and metric-semantic layer of the Situational Graphs (S-Graphs) before navigating in the environment. When the robot navigates in the construction environment, it uses the robot odometry and 3D lidar measurements to extract planar wall surfaces. A particle filter method exploits the previously built situational graph and its available geometric, semantic, and topological information to perform global localization. We validate our approach in simulated and real datasets captured on ongoing construction sites presenting state-of-the-art results when comparing it against traditional geometry-based localization techniques. Full article