In this paper, we consider the case of carrying an object with a quadruped-wheeled robot and examine and verify the angle planning method for the robot’s base link (load section) that suppresses the relative tilt of the carried object. It is important to suppress the tilt of the carried object relative to the base link. We formulated the angle of the base link at which the carried object does not begin to tilt relative to the base link. We examined an angle planning method for the base link that would suppress the relative tilting of the carried object. Then, we verified the method using a simulation and a quadruped-wheeled robot: MELEW-3 (Meiji Leg-Wheeled Robot - No.3). As a result, both in the simulation and on the actual robot, we succeeded in carrying the object without turning over, and the base link was tilted based on the planning method.

With the increasing presence of embodied conversational agents (ECAs) in our daily lives, it is crucial to understand how the degree of their physical embodiment influences user engagement and perception. Previous research has explored this relationship, revealing a tendency for higher embodiment levels to result in better engagement and performance. However, the potential impact of novelty in the ECA experience has yet to be thoroughly investigated, despite being acknowledged in prior studies. To address this research gap, we conducted an experiment where participants interacted with three distinct Social Plantroid embodiment levels and provided ratings of their perception and preference, while engagement was estimated from the volunteers’ facial expressions. Our findings indicate weak to moderate correlations between participants’ experience with robots, engagement, and their perceived characteristics of the ECAs, suggesting that both novelty and physical embodiment play a role in shaping interactions with ECAs.

In this paper, we propose a new brachiation robot, a single-rod brachiation robot. Brachiation is a method of locomotion that makes clever use of gravity and has been tried to apply to robots. Conventional brachiation robots are multiple-pendulum-like robots that mimic a gibbon. Although the multiple-pendulum-like robot can easily change the length of one brachiation step by joints, it has complex structures and generates aperiodic motions such as chaos. In contrast, the single-rod brachiation robot has the advantages of simple structure and the ability to suppress complex multiple-pendulum trajectories. The single-rod brachiation robot has a disadvantage because it is difficult to adjust the distance to the next bar. However, we can solve it by aerial brachiation, which includes an aerial phase before grasping the next bar. Using the actual robot, we showed that the swinging amplitude could be increased by appropriately moving its center of gravity like a trapeze motion. In addition, using this, we achieved continuous brachiation across three bars and brachiation including the aerial phase with a flight distance of 140 mm.

During the COVID-19 pandemic, many research areas that require in person experiments with human volunteers have been impacted due to lockdowns and other activity-restricting policies. The field of robotics is no exception, and specially human-robot interaction research has been severely impacted. In order to circumvent the difficulty of gathering volunteers in person to interact with a robot, we have decided to build a novel crowdsourcing web platform for hosting our "Talk to Kotaro" experiment. The experiment consists of volunteers talking to a robot avatar and reacting to its semantic-free utterances. The developed web platform, which was built using the Python Flask framework, allows for such interactions while recording audio and video and other relevant data, which will be used for studying human impression estimation on gibberish speech. This paper describes not only the experiment and its preliminary results, but the developed platform itself; such tool is essential during pandemics and very useful for regular times, because it enables crowdsourcing data from all over the world.

With the advent of different electronic skins sensitive to touch and robots composed of soft materials, tactile or haptic human-robot interaction is gaining importance. We designed a highly realistic artificial hand aiming to reproduce human-to-human physical contact through a special morphology imitating flesh and bones and a heating system imitating human body temperature. The mechanical response properties of different finger designs were analyzed and the most mimetic one came very close to a human finger. We designed three experiments with participants using haptic exploration to evaluate the human-likeness of: (1) finger morphologies; (2) complete hands: real human vs. soft and warm artificial hand vs. rubber hand (3) the hand mounted on a manipulator with fixed vs. passive compliant wrist in a handshake scenario. First, participants find the mimetic finger morphology most humanlike. Second, people can reliably distinguish the real human hand, the artificial one, and a rubber hand. In terms of humanlikeness (Anthropomorphism, Animacy, and Likeability), the human hand scores better than the artificial hand which in turn clearly outperforms the rubber hand. The temperature, or "warmth", was rated as the most human-like feature of the artificial hand.

Even if a robot is not designed with a specific impression, if there is a means that can add an impression later to the robot, it will be useful for social robot design, we considered. In particular, anthropomorphism seems to be an important impression of designing social interaction between humans and robots. In the movie, ”STAR WARS,” there is a non-humanoid robot, called R2-D2, which communicates mainly by sounds. A humanoid interpreter robot, called C-3PO, responds to the sound of R2-D2 with natural language and gesture. And the audience finds the personality in R2-D2 richer than the personality which is based on the information which R2-D2's sounds have. It might be possible to change the impression of a non-humanoid robot emitting simple sounds by communication with a humanoid robot that speaks a natural language and make gestures. We conducted an impression evaluation experiment. In the condition where robots are interacting, the observer evaluated anthropomorphism of the nonhumanoid robot more than in the non-interacting condition. There were also some other impressions that have changed.

Robots and other autonomous systems interacting with humans should customize their behaviour to their human partner's preferences. We propose a method for learning and generating robot movement customized to individual preferences. Within a reinforcement learning framework, we generate rewards based on facial expressions observed during the robot's motion. Robot motions are parametrized; the rewards are used to modify these motion parameters using Q learning. The proposed approach is evaluated in a user study, using an interactive kinetic sculpture. The system interacts with participants and evolves its motion based on the rewards estimated from the participants' facial expressions. Our results show that, for a subset of participants, the system was able to successfully generate actions that resulted in higher than random rewards. The ability to successfully generate high-reward actions depends on: being able to recognize positive affect from the face, being able to generate actions that are pleasing to the participant, and being able to learn the mapping from rewards to actions.

User preferences for robots differ according to the robot shape and how it moves. This paper proposes a method for generating motions that will be pleasing to a user of a modular robot that can be configured arbitrarily. We propose a preference estimator that uses supervised learning to estimate how well users will like a combination of a motion pattern and robot shape. We also propose a motion selector and a motion generator that select and generate motions in consideration of the balance of the robot's shape and its motion. These methods were tested with a prototype modular robot system and a group of human test subjects who configured the robot as they wished. The proposed motion selector and generator, trained on a preprogrammed set of motion patterns, then presented a ranked set of motions to the subjects. The motion selector proved effective but the motion generator did not. Overall, the proposed system was received favorably by the subjects.

Robots have become required to collaborate with people in real environments. In such collaboration, robots should develop teamwork with people as soon as possible like a capable worker would. Non-verbal behavior plays a crucial role in establishing good team interactions, and it is associated with the influence of facial components such as eyes. However, the necessary facial components of a robot for good human-robot collaboration have not been determined yet. Many robots are designed based on a designer's ideas. Thus, this study focused on blink behavior and an investigation on improving teamwork. To tackle this issue, we used one idea of cognitive science: “Joint action” where interacting agents share what is on their minds. We conducted a Go/Nogo test with 29 participants to determine whether or not interacting participants are sharing their minds with the robot as part of a team. In this study, action space was used as an action representing their minds. The participants performed a task with robots having four eye conditions: Blink-in-sync, independent blinking, no blinking, and without eyes. The results indicated that a robot that exhibited two blinking behaviors made participants' action space move toward the robot because the area which response times were shorter than far area moved from participants' near area to middle area (center) between the participant and the robot.

The main characteristics of service robots are their human-centered working environment and their non-expert users. Therefore, service robots need to exhibit human robot interaction that lets users feel comfortable in order for them to accept these robots at home. In this research, we propose a concept of a kitchen assistant robot supporting people in completing stressful cooking tasks. The stressful cooking tasks in this study are also verified to gain the understanding of the applicability of service robots in a wider sense. For the proposed concept a prototype of the kitchen assistant robot is constructed which consists of a robot arm and a control device Myo gesture armband. 18 university students experienced the prototype by completing the stressful tasks and gave feedback by answering questionnaires. This study investigates the usability and users' acceptance of the kitchen assistant robot.

Is it possible that paintings created by an artificial agent touch a human? We investigate how an artificial agent “creates” paintings and what elements of paintings influence the human feeling. This paper presents the challenge of creating paintings by an artificial agent: a painting creating system. We propose the impression feedback so that an artificial agent can create impressive paintings, not based on retouching or other modification methods. The painting creating system draws a painting and predicts human impressions from the painting. Based on the human impressions, the system redraws another painting repeatedly. The method we propose consists of two modules: a painting generator and an impression estimator. The painting generator creates original paintings with brushstrokes. The impression estimator sees paintings and predicts human impressions with neural networks. This paper describes the method and the modules to construct the painting creating system.

The anthropomorphic body form is a complex articulated system of links/limbs and joints, simultaneously redundant and underactuated, and capable of a wide range of sophisticated movement. The human body and its movement have long been a topic of study in physiology, anatomy, biomechanics, and neuroscience and have served as inspiration for humanoid robot design and control. This survey paper reviews the literature on robotics research using anthropomorphic design principles as an inspiration, at both the design and control levels. Next, anthropomorphic body modeling, motion analysis, and synthesis techniques are overviewed. Finally, key applications arising at the intersection of robotics and human movement science are introduced. The survey ends with a discussion of open research questions and directions for future work.

This paper describes a control method for noncyclic swing motions such as throwing, hitting and kicking in multiple-joint robots by using “time reversal integral.” This method calculates a control input sequence and an initial posture of the robot to reach a designated terminal state by integrating a dynamic system without directly designating trajectories. The terminal end-tip speed is maximized by optimizing the target terminal state under constraints such as friction and the joint position limits. Feasibility of the method is evaluated by ball throwing experiments.

This paper describes a feedback excitation control system with consideration of gravity, which is a control method to obtain high kinetic energy by utilizing passive potential energy. In the case of a robot that has series elastic joints, peak kinetic energy becomes higher than that of a rigid robot with same motors. We have proposed the feedback excitation control for horizontal multiple-joint robots in our previous work. In this paper, we extend the feedback excitation control to systems that are affected by gravity, and we analyze the feedback excitation control system from the viewpoint of linear vibration mode. Validity of the proposed `coordinate or opposite phase controller' is suggested by the modal analysis. We examine effective excitation controllers to utilize gravitational and elastic potential energy by simulations and experiments.

This paper describes analysis and design criteria of the 1-Joint Spring-Motor Coupling System (SMCS). A system including series elastic elements shows vibrational responses in the velocity space, and our concept is to use the velocity peak of the system for motions that need explosive power. By tuning parameters, we can obtain instantaneously higher velocity than without any spring. We constructed a mathematical model of a 1-Joint SMCS (including motor electrical properties) and confirmed the velocity increasing effect on SMCS by numerical analyses and real experiments. And we discovered existence of the most effective inertia balance between the motor shaft and the robot link, and proposed the optimum spring constant with consideration of the moveable range of the link. We confirmed the validity and the limitation of the criteria by the real experiments.

Many humanoids have been developed, but more complicated and flexible humanoids must be developed, in order to realize more natural and various motions like humans. However, it is difficult to measure directly joint posture in the multi-dofs joint of such robots (e.g. a hip spherical joint) because of its complicated structure. This paper describes an estimation method for tendon-driven joint postures of these complicated multi-dofs joints, only based on information of muscles' length relative displacement data during joints movement. We regard this posture estimation problem as a pattern matching problem in the mapping space from joint posture to muscle lengths and solve this problem by using very simple searching algorithms. Furthermore, this paper describes a strategy for deciding muscles motor command to acquire its joint proprioception by the proposed joint posture estimation method only based on information of muscles' length relative displacement data. Finally, we confirmed the feasibility of the proposed estimation method by applying this algorithm to the real tendon-driven musculoskeletal humanoid Kojiro.

In this paper we present a new method for picking up dishes based on active groping. Though a bird's eye view is commonly used to recognize dishes, this method tends to produce errors in the presence of large occlusion, A multisensory robot hand can be used in a kitchen environment to probe and grasp dishes that are placed close to each other. Though sensing is an effective method, it is difficult to recognize a dish globally by this method because of the locality of measurement. To solve this difficulty, we propose a sensing method to aquire the geometric information about dishes by tracing their surface. We demonstrate that a robot can pick up three types of dishes on the basis of this active groping strategy by conducting an experiment.

A method of giving intelligence to control robots by human navigations is one of appropriate solution to respond to a lot of unforeseeable situations, and making movement of complicated robots in contact condition with surroundings is not easy. In this research, a bilateral wearable device using stiffness adjustable muscle actuator modules is developed in order to control robots, feel external force of robots and teach motion that contact on surroundings. For an experiment it was realized maneuvering a musculo-skeletal humanoid, it could feedback humanoid's external force to manipulator and its force feedback by bilateral control leads manipulator to do safety contact motion.

We are developing the novel musculoskeletal humanoid that is able to do coordinated motion with arms, legs and spine. In this research, we present how to realize largely bending/extending motion while standing using spine and hip joints of a fullbody musculoskeletal humanoid, which has a complicated body like a human, such as over 90 muscles and about 60 DOFs. And we propose how to generate coordinated motions of spine and hip joints and how to control such a complicated humanoid in order to keep standing during its motion. Furthermore, we confirmed that this robot could bend/extend its spine and hip joints coordinately while standing by some experiments.

Humanoid robots are still in a process of the evolution. We are trying to develop a next-generation which have safety, flexibility and multiplicity of uses. A shoulder structure is one of the keystone, because it controls arms and end effectors and it have direct contact with humans and daily life environments. We have designed new shoulder structure following the scapula-collarbone structure for a muscle-driven humanoid robot named ldquoKojirordquo (Fig. 1)[1]. We consider that the scapula-collarbone structures have the following merits, 1)wide range of movement, 2)flexible shoulder like humans, 3)safety from the driving system, 4)allowing space for a lot of parts inside the thorax. The shoulder structure is consisted of scapula, collarbone, upper-arm and thorax. We have devised the spherical shape thorax and scapula structure which realizes desired scapula motions. In this paper, we describe the design process and operation test of the shoulder structure.

High physical ability of humanoid robots is desired for application to nursing care. Light and powerful actuators are required to realize the high-power performance. In this paper, we propose a method to bring out maximum performance of electric motors aggressively. The technique of motor core temperature estimation and control improves the motor power performance dramatically but safely without motor burnout. We have developed high power motor driver modules for the proposed method and equipped them into our humanoid robot and prototype jumping robot. High-power performance experiments with the robots demonstrate our method.

This paper presents how to develop a lower body with both redundant and high-powered actuator systems toward the next version of a fully tendon-driven musculoskeletal humanoid, which will be able to realize various flexible motions using whole body. The newly developed lower body has 44 actuators and each actuator can generate 25[kgf] muscle force continually. We propose the new design method of hollowing out the parts assembly areas, which realizes easy design of the skeleton with massive actuators. Finally we presented an experiment on the hip muscles tension and redundancy performances during the hip joint rotation motion.

We are trying to develop an innovative humanoid which learns from the structure of a human shoulder, especially the bladebone and collarbone. We consider that the bladebone-collarbone structures have the following merits, l)wide range of movement, 2)having the shoulder structure built on to the outside of the chest, allowing space for a lot of parts inside the chest, 3) flexible shoulder like humans. In contrast, it is difficult to control the shoulder structure because it have multiple degrees of freedom and extraordinary physical constraints. An aim of our research is to create a repeatable motion generation system of the bladebone-collarbone structures for real musculo-skeletal humanoid robots. In this paper, we describe the design process of the bladebone-collarbone structures for a muscle-driven humanoid robot, and the simulation system considering geometrical constraints of the structures. Then, we show a motion experiment using the shoulder structures of the humanoid, based on the simulation system we presented.

Shape-memory alloy(SMA) is a suitable actuator for a micro mobile robot due to its size and weight. However, length of SMA actuators is known to be nonlinear and hysteretic. We can control SMA’s shape analogously to its electrical resistance. This paper presents a platform to construct high degree of freedom robots with tendons of SMA actuators. We incorporate coil shape SMA as variable length tendons of tendon-driven robots. By controlling electrical resistance of SMA tendons, we can control posture of the robot structure in model-based method. A method to resolve electrical resistance for control from given posture of a high degree of freedom robot by using model of SMA and the robot is proposed. A small electrical system for high D.O.F. robots is also developed. As an application of our system, we show a four-legged robot with 16 D.O.F. joints and 24 SMA tendons.

This paper presents the concepts, issues on development, and future perspectives of a novel musculoskeletal humanoid `Kotaro'. The specifications and advantages of Kotaro include muscle-driven endoskeletal structure, multiple degrees of freedom, variable physical softness, the multiple-joint spine, easily configurable muscles, distributed onbody controllers, various sorts of many sensors including eyes, ears, and whole-body tactile sensors, and so on. These characteristics would achieve a flexible body, litheness of motions, safety, and adaptability and applicability to diverse tasks which would very often appear in human's daily lives

We have been studying about muscle-tendon spined humanoid robots for aiming a novel humanoid robot that has modifiable mechanical flexibility, safety and wide variety of postures. This paper describes a new concept of reinforceable-muscle humanoid and the development of a new musculo-skeletal humanoid robot named "Kenji" that is a prototype muscle-driven humanoid next to previous developed humanoid "Kenta". Kenji has 140 actuators in total and numerous multi-modal sensors. This paper also presents some experiments that show the feasibility of the robot.

We are trying to create an innovative humanoid which has increased flexibility by imitating the structure of a human shoulder, especially the shoulder blade. We designed a flexible shoulder structure for a muscle-driven humanoid robot which has the following merits, 1) wide range of movement and flexible shoulder like humans, 2) having the shoulder structure built on to the outside of the chest, allowing space for a lot of parts inside the chest. We developed a prototype humanoid robot named "Blade" which has a musculo-skeletal humanoid torso with the shoulder blade, driven by motor-actuated tendons. This paper describes the advantages of the structure of the shoulder blade, the development of a humanoid with the shoulder blade, and some experiments showing its range of movement using the prototype humanoid robot we presented.

We propose a concept of reinforceable-muscle humanoid with hyper parallel muscle-tendon systems. By the facilitation of changing the assignment of actuators, we can easily strengthen a specific part of robot body, while changing the arrangement of actuators of current humanoid robots is quite difficult. By developing muscle units in each of which a motor and sensors are integrated, and by adopting musculo-skeletal structure, the rearrangeability of muscles has been realized. This paper describes the concept, prototype design and implementation of the reinforceable muscle humanoid, and the evaluating experiment by a musculo-skeletal humanoid is presented.

Since an environment or body states of robots are very changeable, robotic imitation systems should have ability to develop their behaviors by themselves. For the development of the imitation behaviors, we assume that attention during imitation is the key information. In order to realize such imitation systems with evolving ability, the idea of reinforcement learning system based on the attention structure during imitation has been presented in this paper. First, for describing the attention during imitation behaviors, we define the term 'sensor-action attention pair' as the pair of the most important sensor information and the focused body parts during that behavior. Second, we introduce R-learning, the reinforcement learning method for continual tasks such as imitation behaviors. Third, the method to design the state-action space and the reward function based on the sensor-action attention pair is proposed. At last, for the confirmation of the function of the proposed imitation behavior system, we have done some experiments using actual humanoid Kenta. In those experiments, Kenta can develop imitation behavior that imitates the hand position of the human.

It is very important and hard to develop motions and behaviors for robots that have complex body and numerous actuators and sensors. The more complex a humanoid's body becomes, the more important the developing environment of the motions and behaviors will be. We have built a fully muscle-driven flexible-spine humanoid named "Kenta", which has 96 actuators and more than 400 sensors including tension sensors, posture sensors, vision sensors, and so on. This paper describes the developing environment of motions and behaviors for the robots like Kenta. A visualizable geometric model, a simulation environment transparent to the real environment, sample procedures of the motion development, and, as an example, realization of swing behavior by Kenta are presented.

We are trying to realize a humanoid which has flexibility. If humanoids have a flexible structure, safety and posture variety can be achieved. We focus on the role of the human spine and muscle-driven system. By having a flexible spine, a humanoid will have safety and many degrees of freedom to realize a variety of postures. By driving joints by tension-controllable tendons, flexibility of the joints can be controlled. We developed a whole-body tendon-driven flexible-spine humanoid named "Kenta". This paper describes the design and control of Kenta, focusing on the design of the spine. The spine consists of ten joints, vertebrae and rubber disks, ribs, and forty muscles equipped with tension sensors. We also propose control methods of the spine. One uses a geometric virtual robot model and another is based on direct teaching. Using these methods, some whole-body motions are presented.

The development of a robot which has a flexible spine is presented. By embedding a multi-DOF (degree of freedom) soft structure into a robot body as a spine, the robot can increase its ability to absorb shock and the ability to work in various environments such as narrow places or human fields, and its motion could be more natural. The developed full-body human-form robot has a five-jointed flexible spine. Each joint (vertebra) has 3 DOFs. Between each two vertebrae is a "disk" made of silicone rubber. The spine is controlled by eight tendons, whose tensions can be controlled using tension-sensors and locally distributed microcontrollers. The paper describes the development of the flexible spine and the control of the posture of the spine and body.

In this paper, a second generation remote-brained humanoid robot is presented which is developed for research on whole body action. Humanoid robots are important as a platform for the integration of techniques and algorithms acquired from research on manipulators, legged robots and so on. And they have new problems such as how to acquire, memorize, select and carry out various motions which use their whole bodies efficiently. In order to do research on these problems, a good robot body, which has whole body and enough performance for walking and getting up when it falls down is necessary. At the same time, a powerful brain is necessary which can be evolved through the body. As a solution to these demands, remote-brained approach was proposed and several humanoid robots was developed. Using these robots, several researches were done. For example, a brain framework called BeNet, an action acquisition using GA and NN and so on. They were done using a simple wireless connection. Interface between robot brain and its body to concentrate on a high-level problem. However this interface limited actions the robot can do simultaneously. In this paper, this old interface is taken to the next step. New interface has multiple actuator control methods which are switched on demand, and an onbody microprocessor network which controls actuators, measures sensors and interacts with a brain. Finally a new humanoid robot is developed on this interface.