We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.

An unexpected path reversal is discovered for a serial robot with an offset-axis wrist over a finite range of proximity to the wrist singularity. This is replicated by a kinematic model. A prior spherical-wrist method transits the singularity with limited joint rate and acceleration under a constant rate of tool traversal. Accurate position is maintained by controlling a small deviation in orientation. Extensions to the method for an offset wrist (1) find the least-maximum deviation, (2) identify and locate where a path reversal occurs, and (3) use this point to control step size in a high-order predictor-correction path following procedure.

In this paper, several physical activity-based human–computer interaction (HCI) games which are developed and implemented for the improvement of attention, emotion, and sensory–motor coordination will be presented. The interface and the difficulty levels of these games are specially designed for the use of people with different age groups and disabilities. The games involve physical activities for the fulfillment of some basic HCI tasks which require hand and arm motion for control, such as fruit picking and air hockey, with adaptive difficulty levels based on varying parameters of the games and human performance. In the fruit picking game, several fruit images are moving from top to the bottom of the screen. Objective is to collect apples while avoiding the pears. The player’s hand will control the basket that collects the fruits. In the air hockey game, the player will try to score goals against computer-controlled opponent. The player’s hand will control the paddle to hit the puck to score or to defend his/her goal area. The player’s hand is recognized by Kinect RGB-D sensors in both games. Aim of the adaptive difficulty-based system is keeping the players engaged in the games. The games are tested with a group of deaf children (3.5–5 years) as a part of an ongoing project,1 to decrease the stress of the children and increase their positive emotions, attention, and sensory–motor coordination before the audiology tests. The game performances and the evaluation of the therapists show that the games have a positive impact on the children. The games are also tested with a group of adults as a control group, where a mobile EEG device is employed to detect the attention levels. For this purpose, the adults also attended a third game featuring a maze and controlled with Myo sensors.

Suppose in a given planar circular region, there are smart mobile evaders and we want to find them using sweeping agents. We assume the sweeping agents are in a line formation whose total length is predetermined. We propose procedures for designing a sweeping process that ensures the successful completion of the task, thereby deriving conditions on the sweeping velocity of the linear formation and its path. Successful completion of the task means that evaders with a given limit on their velocity cannot escape the sweeping agents. We present results on the search time given the initial conditions.

Double inverted pendulum model, stationary or on a cart, is computationally the simplest out of the range of reasonable models used for anthropomorphic robots motion synthesis. However, it is still not sufficient for describing more complex situations. The novel concept of variable double inverted pendulum (VDIP) for static postures and VDIP on cart (VDIPC) for dynamic cases is proposed. It provides a simplified but a sufficiently accurate tool for planning the human-like static and dynamic robot postures. Its variable parameters enable the description of both human static postures and motion dynamics. The variable length of the lower link is essential for the representation of postures attained by bending legs. The studies of a set of static and dynamic postures were used for deducing and verifying the locations of lower and upper joint of a double pendulum and the point masses. To justify the concept, human body and pendulum behaviors are compared taking into account a typical model of the human body. Static analysis was conducted by considering static human postures. Dynamic conditions were analyzed using the data acquired from human motion and thus the VDIPC definition was established. The zero moment point trajectories of the human and of VDIPC were compared, validating the correctness of VDIPC in dynamic situations. The formal description of VDIPC is provided together with the torques equilibrium condition needed for evaluating the dynamic postural stability, with the VDPIC representing the robot configuration. The VDPIC state equations are formulated in a form required by the predictive control method. The paper contributes to the motion synthesis methods of anthropomorphic robots taking into account postural control.

Dynamic movement primitives (DMP) are motion building blocks suitable for real-world tasks. We suggest a methodology for learning the manifold of task and DMP parameters, which facilitates runtime adaptation to changes in task requirements while ensuring predictable and robust performance. For efficient learning, the parameter space is analyzed using principal component analysis and locally linear embedding. Two manifold learning methods: kernel estimation and deep neural networks, are investigated for a ball throwing task in simulation and in a physical environment. Low runtime estimation errors are obtained for both learning methods, with an advantage to kernel estimation when data sets are small.

Cooperative transportation by human and robotic coworkers constitutes a challenging research field that could lead to promising technological achievements. Toward this direction, the present work demonstrates that, under a leader–follower architecture, where the human determines the object’s desired trajectory, complex cooperative object manipulation with minimal human effort may be achieved. More specifically, the robot estimates the object’s desired motion via a prescribed performance estimation law that drives the estimation error to an arbitrarily small residual set. Subsequently, the motion intention estimation is utilized in the object dynamics to determine the interaction force between the human and the object. Human effort reduction is then achieved via an impedance control scheme that employs the aforementioned estimations. The feedback relies exclusively on the robot’s force/torque, position as well as velocity measurements at its end effector, without incorporating any other information on the task. Moreover, an adaptive control scheme is adopted to relax the need for exact knowledge of the object dynamics. Finally, an extension for multiple robotic coworkers is studied and verified via simulation, while extensive experimental results for the single robot case clarify the proposed method and corroborate its efficiency.

This paper presents a novel solution for precision draping of prepreg composite fabrics onto double curved molds. Our contributions relate to system design, including hardware and software components, and to system integration. On the hardware side, design and implementation of a drape tool with up to 120 suction cups positioned individually by linear actuators are described. On the software side, design and implementation of the software architecture are presented, along with necessary algorithms within sensor technologies and mathematical modeling. The essential system’s components were verified individually, and the entire integrated system was successfully validated in the Proof-of-Concept experiments, performed on an experimental physical model of the system.

The authors summarize the main dynamic balancing methods of robotic mechanisms in this paper. The majority of dynamic balancing methods have been presented, and there may be other dynamic balancing methods that are not included in this paper. Each of the balancing methods is reviewed and discussed. The advantages and disadvantages of each method are presented and compared. The goal of this paper is to provide an overview of recent research in balancing. The authors hope that this study can provide an informative reference for future research in the direction of dynamic balancing of robotic mechanisms.

With the increasing demand for humans and robots to collaborate in a joint workspace, it is essential that robots react and adapt instantaneously to unforeseen events to ensure safety. Constraining robot dynamics directly on SE(3), that is, the group of 3D translation and rotation, is essential to comply with the emerging Human–Robot Collaboration (HRC) safety standard ISO/TS 15066. We argue that limiting coordinate-independent magnitudes of physical dynamic quantities at the same time allows more intuitive constraint definitions. We present the first real-time capable online trajectory generator that constrains translational and rotational magnitude values of 3D translation and 3D rotation dynamics in a singularity-free formulation. Simulations as well as experiments on a hardware platform show the utility in HRC contexts.

The purpose of our study was to get deeper insights into sprinting with and without running-specific prostheses and to perform a comparison of the two by combining analysis of known motion capture data with mathematical modeling and optimal control problem (OCP) findings. We established rigid multi-body system models with 14 bodies and 16 degrees of freedom in the sagittal plane for one unilateral transtibial amputee and three non-amputee sprinters. The internal joints are powered by torque actuators except for the passive prosthetic ankle joint which is equipped with a linear spring–damper system. For each model, the dynamics of one sprinting trial was reconstructed by solving a multiphase least squares OCP with discontinuities and constraints. We compared the motions of the amputee athlete and the non-amputee reference group by computing characteristic criteria such as the contribution of joint torques, the absolute mechanical work, step frequency and length, among others. By comparing the amputee athlete with the non-amputee athletes, we found reduced activity in the joints of the prosthetic limb, but increased torques and absolute mechanical work in the arms. We also compared the recorded motions to synthesized motions using different optimality criteria and found that the recorded motions are still far from the optimal solutions for both amputee and non-amputee sprinting.

This study investigates the effectiveness of a robot-mediated strategy aimed at promoting balance recovery after multidirectional slippages. Six older adults were asked to manage anteroposterior and mediolateral slippages while donning an active pelvis orthosis (APO). The APO was set up either to assist volunteers during balance loss or to be transparent. The margin of stability, in sagittal and frontal planes, was the main metric to assess the effectiveness of balance recovery. Results showed that the assistive strategy is effective at promoting balance recovery in the sagittal plane, for both perturbing paradigms; however, it is not effective at controlling stability in the frontal plane.

Wearable devices are fast evolving to address mobility and autonomy needs of elderly people who would benefit from physical assistance. Recent developments in soft robotics provide important opportunities to develop soft exoskeletons (also called exosuits) to enable both physical assistance and improved usability and acceptance for users. The XoSoft EU project has developed a modular soft lower limb exoskeleton to assist people with low mobility impairments. In this paper, we present the design of a soft modular lower limb exoskeleton to improve person’s mobility, contributing to independence and enhancing quality of life. The novelty of this work is the integration of quasi-passive elements in a soft exoskeleton. The exoskeleton provides mechanical assistance for subjects with low mobility impairments reducing energy requirements between 10% and 20%. Investigation of different control strategies based on gait segmentation and actuation elements is presented. A first hip–knee unilateral prototype is described, developed, and its performance assessed on a post-stroke patient for straight walking. The study presents an analysis of the human–exoskeleton energy patterns by way of the task-based biological power generation. The resultant assistance, in terms of power, was 10.9% ± 2.2% for hip actuation and 9.3% ± 3.5% for knee actuation. The control strategy improved the gait and postural patterns by increasing joint angles and foot clearance at specific phases of the walking cycle.

This study presents an optimal design procedure including topology optimization and size–shape optimization methods to maximize mechanical advantage (which is defined as the ratio of output force to input force) of the synthesized compliant mechanism. The formulation of the topology optimization method to design compliant mechanisms with multiple output ports is presented. The topology-optimized result is used as the initial design domain for subsequent size–shape optimization process. The proposed optimal design procedure is used to synthesize an adaptive compliant gripper with high mechanical advantage. The proposed gripper is a monolithic two-finger design and is prototyped using silicon rubber. Experimental studies including mechanical advantage test, object grasping test, and payload test are carried out to evaluate the design. The results show that the proposed adaptive complaint gripper assembly can effectively grasp irregular objects up to 2.7 kg.

Path planning under 2D map is a key issue in robot applications. However, most related algorithms rely on point-by-point traversal. This causes them usually cannot find the strict shortest path, and their time cost increases dramatically as the map scale increases. So we proposed RimJump to solve the above problem, and it is a new path planning method that generates the strict shortest path for a 2D map. RimJump selects points on the edge of barriers to form the strict shortest path. Simulation and experimentation prove that RimJump meets the expected requirements.

In this article, a two-dimensional analysis of biped robot sliding dynamics is performed. First, the dynamics of a biped robot based on feet-slip are derived using the coulomb friction model. The state transition can be formulated in the centroid acceleration space whose diagram is defined as a “triangle of sliding friction” (TSF). The TSF's characteristics are explained by focusing on comparison with the cone of friction which has a similar state decision diagram. Next, for the behavioral simulation of a concrete model, a 2-DOF biped robot is used to analyze the sliding features in terms of the asymmetry of the dynamics of each leg. Finally, the sliding characteristics are applied to the two tasks of running and somersaulting. The results show the robot takes short rapid repetitive steps for running based on frictional asymmetry and theoretically based on torque asymmetry can make one revolution using the large angular momentum acquired during sliding motion.

This paper proposes an alternative environment mapping method for accurate robotic navigation based on 3D information. Typical techniques for 3D mapping using occupancy grid require intensive computational workloads in order to both build and store the map. This work introduces an Occupancy-Elevation Grid (OEG) mapping technique, which is a discrete mapping approach where each cell represents the occupancy probability, the height of the terrain and its variance. This representation allows a mobile robot to know with an accurate degree of certainty whether a place in the environment is occupied by an obstacle and the height of such obstacle. Thus, based on its hardware characteristics, it can make calculations to decide if it is possible to traverse that specific place. In general, the map representation introduced can be used in conjunction with any kind of distance sensor. In this work, we use laser range data and stereo system data with a probabilistic treatment. The resulting maps allow the execution of tasks as decision making for autonomous navigation, exploration, localization and path planning, considering the existence and the height of the obstacles. Experiments carried out with real data demonstrate that the proposed approach yields useful maps for autonomous navigation.

The paper considers the problem of motion planning and posture control of multiple n-link doubly nonholonomic mobile manipulators in an obstacle-cluttered and bounded workspace. The workspace is constrained with the existence of an arbitrary number of fixed obstacles (disks, rods and curves), artificial obstacles and moving obstacles. The coordination of multiple n-link doubly nonholonomic mobile manipulators subjected to such constraints becomes therefore a challenging navigational and steering problem that few papers have considered in the past. Our approach to developing the controllers, which are novel decentralized nonlinear acceleration controllers, is based on a Lyapunov control scheme that is not only intuitively understandable but also allows simple but rigorous development of the controllers. Via the scheme, we showed that the avoidance of all types of obstacles was possible, that the manipulators could reach a neighborhood of their goal and that their final orientation approximated the desired orientation. Computer simulations illustrate these results.

Changes in world-wide population trends have provided new demands for new technologies in areas such as care and rehabilitation. Recent developments in the the field of robotics for neurorehabilitation have shown a range of evidence regarding usefulness of these technologies as a tool to augment traditional physiotherapy. Part of the appeal for these technologies is the possibility to place a rehabilitative tool in one's home, providing a chance for more frequent and accessible technologies for empowering individuals to be in charge of their therapy.

Objective: this manuscript introduces the Supervised Care and Rehabilitation Involving Personal Tele-robotics (SCRIPT) project. The main goal is to demonstrate design and development steps involved in a complex intervention, while examining feasibility of using an instrumented orthotic device for home-based rehabilitation after stroke.

Methods: the project uses a user-centred design methodology to develop a hand/wrist rehabilitation device for home-based therapy after stroke. The patient benefits from a dedicated user interface that allows them to receive feedback on exercise as well as communicating with the health-care professional. The health-care professional is able to use a dedicated interface to send/receive communications and remote-manage patient's exercise routine using provided performance benchmarks. Patients were involved in a feasibility study (n=23) and were instructed to use the device and its interactive games for 180 min per week, around 30 min per day, for a period of 6 weeks, with a 2-months follow up. At the time of this study, only 12 of these patients have finished their 6 weeks trial plus 2 months follow up evaluation.

Results: with the “use feasibility” as objective, our results indicate 2 patients dropping out due to technical difficulty or lack of personal interests to continue. Our frequency of use results indicate that on average, patients used the SCRIPT1 device around 14 min of self-administered therapy a day. The group average for the system usability scale was around 69% supporting system usability.

Conclusions: based on the preliminary results, it is evident that stroke patients were able to use the system in their homes. An average of 14 min a day engagement mediated via three interactive games is promising, given the chronic stage of stroke. During the 2nd year of the project, 6 additional games with more functional relevance in their interaction have been designed to allow for a more variant context for interaction with the system, thus hoping to positively influence the exercise duration. The system usability was tested and provided supporting evidence for this parameter. Additional improvements to the system are planned based on formative feedback throughout the project and during the evaluations. These include a new orthosis that allows a more active control of the amount of assistance and resistance provided, thus aiming to provide a more challenging interaction.

This paper formulates a new scalable algorithm for motion planning and control of multiple point-mass robots. These autonomous robots are designated to move safely to their goals in a priori known workspace cluttered with fixed and moving obstacles of arbitrary positions and sizes. The control laws proposed for obstacle and collision avoidance and target convergence ensure that the equilibrium point of the given system is asymptotically stable. Computer simulations with the proposed technique and applications to a team of two planar (RP) manipulators working together in a common workspace are presented. Also, the robustness of the system in the presence of noise is verified through simulations.