This paper introduces a novel method for controlling multirotor aerial robots connected by passive flexible elements. Despite the growing popularity of multirotor aerial robots, their real-world applications remain limited due to difficulties adapting to complex environments. Soft robotics, due to its inherent flexibility, offers a potential solution, although research on integrating flexible elements into aerial robots is still in the early stages. In this study, we propose control methods for a system where multiple aerial robots are interconnected with passive flexible elements. These robotic systems enhance adaptability, enabling tasks like object manipulation. We model the flexible parts using the piecewise constant strain (PCS) model, which allows for model-based closed-loop control and stabilizes various configurations of the system. Through simulations and experiments, we validated that the proposed method achieves both stable flight and flexible deformation. Notably, we succeeded in maintaining stable flight, which traditional methods could not achieve, and demonstrated both positional controllability and the ability of the flexible parts to bend dynamically during flight.

Human crowd simulation in virtual reality (VR) is a powerful tool with potential applications including emergency evacuation training and assessment of building layout. While haptic feedback in VR enhances immersive experience, its effect on virtual walking behavior in dense and dynamic pedestrian flows is unknown. Through a user study, we investigated how haptic feedback changes user walking motion in crowded pedestrian flows in VR. The results indicate that haptic feedback changed users’ collision avoidance movements, as measured by increased walking trajectory length and change in pelvis angle. The displacements of users’ lateral position and pelvis angle were also increased in the instantaneous response to a collision with a non-player character (NPC), even when the NPC was inside the field of view. Haptic feedback also enhanced users’ awareness and visual exploration when an NPC approached from the side or back. Furthermore, variation in walking speed was increased by the haptic feedback. These results suggest that the haptic feedback enhances users’ sensitivity to collisions in VR environments.

Flexibility and softness play a significant role in dynamic human motions. This includes the flexibility owing to ligaments in the human body and the softness of external structures such as a leaf-spring-type prosthesis. Thus, robotic systems need to utilize such flexibility to achieve dynamic and energy-efficient motion. In this study, we proposed a compliance optimization-based control framework for a rigid-soft hybrid robot system where the continuous deformation of a flexible structure is represented using the piece-wise constant strain (PCS) model. We divided the hybrid system into two states: single support and double support. We validated the proposed method in these states using forward dynamics simulations, assuming a hybrid link system that consists of a humanoid robot with a flexible prosthesis.

In situations where robots work alongside humans, they must be capable of responding flexibly to unexpected external forces. To address this challenge, researchers have conducted numerous studies on soft robotics. However, most of the soft hands studied so far are powered by pneumatic pressure and can only exert pressure up to a several hundred kPa, resulting in low output. To solve this problem, we have developed a hydraulic soft hand in our previous research. In this paper, we derive the relationship between driving pressure, bending angle, and grasping force of a soft hand with a reservoir to evaluate the effect of a rubber sheet reservoir. Additionally, we experimentally show that the soft hand provides grasping flexibility when angle control is applied using the model proposed in this paper.

Pedestrian flow simulation is important to predict congestion in an urban area and prevent a crowd accident. Many studies have used the machine learning-based pedestrian flow model, which require a measurement of pedestrians to obtain training data. Not only the positional data of each person but also pose and body shape information is useful because it enables the model to learn pedestrian features implicitly including age, gender and social relationship. In this study, we present a video motion capture method that estimates correspondences of an unspecified number of pedestrians in different camera images using the body shape feature of Skinned Multi-Person Linear (SMPL) model. Simultaneously optimizing the correspondence, position, pose and body shape, we can find the same person in multiple cameras and reconstruct their poses and body shapes. We quantitatively compare the result of the method with that of an optical motion capture and qualitatively evaluate the method using an open dataset of pedestrians.

Congestion in urban spaces sometimes leads to serious accidents. To prevent a congestion and serious accident, it is important to properly arrange building-layouts and guide pedestrians safely based on mathematical modeling and simulation of pedestrian flows. In the real world, however, each pedestrian’s behavior is so complicated and often includes spatio-temporally multiscale decision making while most of existing studies mainly focused on a limited local area. In a previous report, a trained model could simulate some pedestrian trajectory, but it also generated undesirable behavior that a pedestrian ignored a traffic light. In this study, we introduce an attention mechanism to solve this problem. The performance of the model is evaluated quantitatively by the prediction error and qualitatively by visualizing the time of a traffic light switching.

In this study, we develop a hydraulically-driven soft robotic hand for handling heavy vegetables in a vegetable factory and report its experimental validations. The working population in agriculture is decreasing worldwide, creating a lot of demands for the robotic automation in harvest and trans-portation of agricultural produces. In particular, a vegetable factory deals with large and heavy vegetables, e.g., cabbages, with 2–3 kg weight and 20–30 cm diameter. A soft robot hand is suitable for handling a food or vegetable; however, most of existing soft robot hands cannot generate necessary output because they are usually actuated by the air-pressure. Therefore, we employ the hydraulic actuation for our soft hand to generate 1 or 2 MPa pressure. Using the developed soft hand, we report experimental validations including basic control performance evaluation and grasping experiments assuming a vegetable factory environment.

As a basic part of the centroidal dynamics, an-gular momentum plays a critical role in humanoid motion control. Therefore, how to explicitly express and control an-gular momentum through whole-body motion is an important topic for researchers. This study discusses the selection of the generalized velocity corresponding to whole-body angular momentum. Based on the discussion, we present a method that decouples the inertia effect in centroidal angular momentum and applies it in resolved viscoelasticity control, which achieves the angular momentum control by whole-body compliance in an interpretable way without complicated calculation. At last, we validate the feasibility and effectiveness of proposed method in forward dynamics simulation of balancing control in the double and single support states and landing motion after hopping.

In this study, we present a framework to en-sure seamless transition in humanoid push recovery involving hopping strategy. We propose a method to adaptively change the time constant that integrated the ankle strategy and variable height strategy. This framework excites a hopping motion against a large disturbance, which provides a seamless transition from the variable height to the hopping strategies. We analyze the applicable region of each strategy based on the simplified model. Moreover, we show that the hopping strategy prevents falling through whole-body dynamic simulations.

Industrial robots require force controllability and impact resistance to ensure safe physical interactions. An electro-hydrostaic actuator (EHA) is expected to be suitable for such applications because it has high backdrivability which improve both force controllability at contact and impact resistance. However, EHAs had been rarely used in multi-axes robotic systems. The previous works validated the force controllability of the EHA-driven robot Hydra. However, the impact resistance of an EHA-driven robot is still unclear. In order to evaluate the impact resistance of the high-power EHA-driven robot, we developed high-pressure EHAs employing ceramics as rigid material to reduce internal leakage, and developed the EHA-driven 6-DOF robot arm Hydracer as the platform for the evaluation. This paper describes the mechanism of Hydracer especially on the base 3-DOF mechanism, and conducts the backdrivability measurement and the impact resistance evaluation.

In this study, we present an application of the Piece-wise Constant Strain (PCS) model to a flexible deformation analysis of a sports prosthesis leg. Dynamic motion analysis of an athlete wearing a sports prosthesis is important to clarify a relationship between the prosthesis characteristics and the performance of an athlete, which contributes to training of an athlete or design of the prosthesis. However, there are few studies on modeling of the three-dimensional deformation of the sports prosthesis. In soft robotics, the PCS model was proposed for calculating a flexible deformation of a beam or rod structure with a low computational cost. We employ the PCS model to calculate the flexible deformation of the prosthesis, assuming that its structure can be discretized into a finite number of segments. Moreover, we propose an estimation method of the prosthesis stiffness using optical motion capture data and calculating the semi-definite programming.

This article proposes a new stability criterion for biped walking systems on the linear inverted pendulum model, in which the dynamic relationship between the center of mass (CoM) and the zero moment point (ZMP) is dealt with. More precisely, based on the fact that a biped walking robot is stable if its ZMP is always located in the supporting region, we consider whether the ZMP error between its reference and real values stays inside a certain area to guarantee the stability condition. To this end, a norm-based new stability criterion is introduced, in which the temporal supremum of the ZMP error is concerned. Regarding the applicability of the stability criterion, we propose two control approaches to biped walking systems with the consideration of the norm-based stability criterion. In other words, full-state and observer-based feedback control approaches are analyzed in this article, and the initial CoM conditions with respect to the stability criterion are obtained for the two control approaches. We call the sets derived by such conditions the stability regions. Toward a more practical significance, we also deal with the effect of unknown disturbances and sensor noises on the stability of biped walking systems. More importantly, even though computing stability regions intrinsically involves an infinite number of linear inequalities, all the stability regions are shown to be explicitly obtained through only finite numbers of computations in this article. Finally, some simulation results are provided to demonstrate the validity as well as the practical applicability of the developed computation methods.

This article discusses a compliance optimization approach that satisfies positive definiteness. Physical human–robot interactions are an important topic in robotics, for which force or compliance control is a key technology. Operational space control (OSC) is one of the most common approaches for robot force control with redundant degrees of freedom. By linearizing OSC, we can derive joint stiffness and viscosity matrices equivalent to the OSC. For an appropriate control, it is important that these matrices are positive definite. However, the stiffness matrix equivalent to the OSC is not always positive definite. In this case, a high kinetic energy is required, which is a problem in terms of the control performance. Therefore, the control performance can be improved by explicitly considering the positive definiteness of the stiffness or compliance. In this article, the authors derive a dynamically consistent compliance formulation and propose a compliance optimization that satisfies positive definiteness. The space of the symmetric positive definite matrix is a Riemannian manifold. We show that minimizing the Riemaniann geodesic distance results in a better performance compared with using OSC. The proposed method is validated via forward dynamics simulations and experiments using a hydrostatically driven humanoid Hydra.

This study presents dynamics computation and control of a hybrid multi-link system that integrates rigid- and soft-bodies. It is a challenging problem to install a softness in a robot system, which is an important factor in human body. Softness achieved by human muscles and ligaments contributes to dynamic motion. Flexibility of a sports prosthetic leg allows a handicapped person to run. However, traditional algorithms of dynamics computation for a robot system or human skeletal model only consider a rigid-body multi-link system. Recent progress in soft robotics such as piecewise constant strain (PCS) model provides the way to compute dynamics of soft deformation with a low computational cost. We construct a hybrid multi-link system integrating rigid-body and the PCS model. For controlling a humanoid robot with soft links, we implement a dynamics computation with a floating-base and derive the center-of-gravity Jacobian matrix of the hybrid link system. Moreover, we demonstrate a forward dynamics simulation of a humanoid robot with prosthetic legs.

6-DOF robot manipulator Hydracer was developed to gain high output torque and high backdrivability by adopting electro-hydrostatic actuators, however control of overall system of Hydracer is not yet conducted. To achieve flexible force control of Hydracer, we worked on the system improvements: enhancement of reliability of ceramics components, reduction of internal leakage by considering the property of hydraulic oil, and the identification of inertial parameters to improve its controllability. By using identified parameters, flexible force control of Hydracer by zero-torque control with gravity compensation was realized which reveals the potential of safe human-robot interaction.

This paper describes a stable knee-stretched walking of a humanoid by the resolved viscoelasticity control (RVC). The RVC method resolves multiple viscoelasticities in task-space, including the center of mass viscoelasticity for balancing, into joint-space viscoelasticity. Although a robust and compliant motion was achieved by the RVC method in previous studies, the conventional knee-bent posture to avoid the kinematic singularity suffered large knee joint torque. In this study, we propose an extension of the RVC capable of the kinematic singularity. We demonstrate through simulations and experiments that the RVC method considering the singularity achieves a stable and human-like walking, reducing the knee joint torque and improving the energy efficiency.

It is still an open problem to develop a reduced order model of bipedal walking that closely represents the complex dynamics of humanoid robots. In this paper, we propose control methodologies, removing both the constant CoM height constraint and the constant centroidal angular momentum constraint. We define a capturability criterion. and propose an enhanced intrinsically stable model predict control to fulfill this new capturability criterion. Then the angular momentum can be controlled. The results of simulations using humanoid robot HRP-4 show the proposed methods can improve the stability of bipedal locomotion on uneven terrains.

This paper discusses the resolved viscoelasticity control (RVC) method that explicitly considers the structure-variability for a humanoid. In a previous report, the author proposed resolving the virtual viscoelasticity at the center of gravity into the joint viscoelasticity considering redundant degrees of freedom, and named this method as RVC. However, the author considered only the single support phase; therefore, the humanoid could be regarded as an open kinematic chain and the RVC was implemented easily. In this paper, the author extends the previous work on the RVC by considering structure-variability - the method now considers an open kinematic chain in the single support phase and a closed kinematic chain in the double support phase. This extension helps realize stable and robust walking motion on uneven terrains. The proposed method is validated using forward dynamics simulations.

This paper proposes the concept of the center of gravity (COG) viscoelasticity to associate joint viscoelasticity with the COG-zero moment point (ZMP) model of humanoid dynamics. Although COG viscoelasticity is based on the well-known kinematic relationship between joint stiffness and end-effector stiffness, it provides practical advantages for humanoid motion control. Once the feedback gain in the COG-ZMP model is designed using the control theory, COG viscoelasticity can be applied to directly transform it to joint viscoelasticity. The author names this method as resolved COG viscoelasticity control (RCVC). In particular, this paper proposes RCVC in which the null-space of the COG Jacobian is employed. The validity of the RCVC is verified by simulating whole-body dynamics.

This paper addresses a novel computation method of the Maximal Output Admissible (MOA) set for a limit cycle controller and its application to motion transition. By approximately calculating the MOA set via sample point cloud, we can obtain an analytic form of the MOA set even on a nonlinear system. Formulation provided in this paper can be applicable to various types of controllers. Using the MOA set, we demonstrate a motion transition from a standing posture to steady walking. Switching two types of controllers based on the MOA set realizes motion transition with the COP constraint satisfied. The validity of proposed method is verified with a simulation.

This paper addresses falling prevention by a humanoid robot which adaptively switches a standing balance controller and a hopping motion controller. In the previous research, the author proposed a switching framework between a standing balance controller and stepping motion controller based on the Maximal Output Admissible (MOA) set. Different from stepping or walking motion, a hopping motion requires control of the COG in the vertical direction. In this paper, the MOA set is extended so as to deal with the vertical COG dynamics. The effectiveness is validated with a simulation of falling prevention.

Humanoid robots have been considered as a universal machine which can operate in place of human. This kind of universal machine requires human-like biped walking capability. In particular, it is important to avoid falling by appropriately switching behaviors even if there are unknown disturbances. The authors proposed the maximal output admissible (MOA) set for the center of gravity (COG) regulator in the upright position. Based on the MOA set, we can switch feedback gains with the Zero Moment Point (ZMP) constraint satisfied. In this paper, the author extends MOA set framework to trajectory tracking controller. This extension makes it possible to switch controllers: regulator in the upright position and tracking controller of a stepping motion in order to avoid falling. The effectiveness of the proposed method is verified with a simulation.

In the densely-populated urban areas, pedestrian flows often cross each other and congestion occurs. It may cause discomfort feeling or pedestrian accidents. In order to reduce the congestion or the risk of accidents, it is required to control swarm flows of pedestrian. This paper proposes an implicit control method of the crossing pedestrian flows. Pedestrian flow is modeled with the continuum fluid model and its congestion degree is calculated as the fluid density. From a simulation of the crossing flows with the continuum model, it is verified that diagonal stripe pattern of the congestion degree emerges. Moreover, the authors propose an implicit control method to improve average flow velocity by moving guides. Focusing on periodic phenomenon of the crossing flows, we investigate the relationship between its temporal and spatial frequency and a periodic motion of guides. From this relationship, a control method based on the temporal and spatial frequency is proposed.

In an exhibition space, it is possible to control human flow implicitly by changing a layout of exhibits. The objectives of this paper are the layout optimization of exhibits to reduce congestion and the amenity space design. For these purposes, macro modeling of human swarm behavior and the optimization method of a layout of exhibits are required. So far, human swarm behavior has been modeled by two-dimensional vector field and individual behavior is represented by dynamics including collision avoidance vector of individuals. In this paper, we extend the human model to multi-dimensional dynamics in order to represent individual characteristics in measured data and visitors' stopping to view exhibits. In addition, a layout of exhibits is optimized based on the proposed model by minimizing collision avoidance vector. The proposed method is verified by simulations and experiments using swarm robots which consist of autonomous mobile robots and radio controlled robots. The results show that the comfortable exhibition space is designed.

Humanoid robots should be able to stand and walk in the presence of external disturbances. This paper addresses the robustness of a humanoid robot to unknown disturbances. Applying the maximal CPI set, it becomes possible to consider the physical constraint explicitly in the COG-ZMP inverted pendulum model control. In our previous research, the convergence speed of COG was improved by applying the switching control based on the maximal CPI set to the stabilization control assuming the contact region is constant. This paper presents updating calculation method of the maximal CPI set when the contact region changes, and the authors propose a falling avoidance control as an application of it. Detecting the stepping necessity based on the maximal CPI set enables to unify the upright position stabilization and stepping motion for falling avoidance. The validity of the proposed method is verified with experiments.

This paper presents a dynamics simulator that can handle complex robotic systems including position-controlled joints and closed kinematic chains. We first extend our prevous algorithm for linear-time forward dynamics algorithm to handle closed kinematic chains. The extended algorithm is formally presented for the first time. We then present another extension that allows position-controlled joints, whose angles exactly follow the reference by perfect servo controllers. This feature is often useful for simple trial simulations only using joint angle commands because the user does not have to design low-level servo controllers for simulation. The simulation can also be performed without precise friction parameters. The algorithm is tested on a humanoid robot having toe joints with four-bar linkage structure.

Communication skill is essential for social robots in various environments such as homes, offices, and hospitals, where the robots are expected to interact with humans. In this paper, we model the primitive nonverbal communication between two persons by mimetic communication model. The model consists of three groups of hidden Markov models (HMMs) hierarchically combined to recognize motions of the human and to generate the interactive motions of the robot. HMMs in the lower layer abstract the motion patterns and HMMs in the upper layer represent the interaction patterns. We demonstrate the validity of this model through kick boxing match between a motion-captured human and humanoid robot, where the robot can autonomously generate its motion in response to attacks by the human

A design methodology to build miniature humanoid robots is discussed. Although light and small bodies would make aggressive types of motion experiments much safer and smoother, they would often cause self-collisions and even restrict the space to mount mechatronic components. In order to defeat some kinematic difficulties including the former issue, a technique to modularize and assign joints is proposed through our prototyped robot. And, as a solution against the latter issue, a portable core control unit which stores a stand-alone electronic system is also introduced through the second version of our humanoid, whose system centers around it.