To implement successful bipedal locomotion in a robot, its center of pressure (CoP) is placed on a supporting area. To achieve locomotion, many studies have focused on the lower body. Given that the human upper body has a large mass and its behavior influences locomotion even in the case of the robot, this study investigates the effect of the upper body, which contains moving arms and a twisting trunk, on CoP. The dynamics is analyzed using a simple model that has a passive viscoelastic trunk joint around the vertical axis and arms that oscillates back and forth. From the derivations of CoP and trunk joint trajectory, three important findings are made: (i) the CoP oscillates along the lateral direction only when the arm swings in an anterior-posterior asymmetric manner, (ii) the trajectories of CoP and trunk joint are in anti-phase, (iii) the phase of CoP along the lateral direction is influenced by the swinging cycle and viscoelasticity of the trunk joint, the mechanical elements of the upper body. An experiment using a robot verified the first and second findings, and simulation verified the last finding. The last finding will contribute to making a feedback controller that converges to the desired phase, which is an important factor for successful bipedal locomotion.

Legged robots have excellent terrestrial mobility for traversing diverse environments and, thus, have the potential to be deployed in a wide variety of scenarios. However, they are susceptible to falling and leg malfunction during locomotion. Although the use of a large number of legs can overcome these problems, it makes the body long and leads to many legs being constrained to contact with the ground to support the long body, which impedes maneuverability. To improve the locomotion maneuverability of such robots, this study focuses on dynamic instability, which induces rapid and large movement changes, and uses a 12-legged robot with a flexible body axis. Our previous work found that the straight walk of the robot becomes unstable through a Hopf bifurcation when the body-axis flexibility is changed, which induces body undulations. Furthermore, we developed a simple controller based on the Hopf bifurcation and showed that the instability facilitates the turning of the robot. In this study, we newly found that the straight walk becomes unstable through a pitchfork bifurcation when the body-axis flexibility is changed in a way different from that in our previous work. In addition, the pitchfork bifurcation induces a transition into a curved walk, whose curvature can be controlled by the body-axis flexibility. We developed a simple controller based on the pitchfork bifurcation characteristics and demonstrated that the robot can perform a turning maneuver superior to that with the previous controller. This study provides a novel design principle for maneuverable locomotion of many-legged robots using intrinsic dynamic properties.

Passive dynamic walking is a model that walks down a shallow slope without any control or input. This model has been widely used to investigate how stable walking is generated from a dynamic viewpoint, which is useful to provide design principles for developing energy-efficient biped robots. However, the basin of attraction is very small and thin, and it has a fractal-like complicated shape. This makes it difficult to produce stable walking. Furthermore, the passive dynamic walking shows chaotic attractor through a period-doubling cascade by increasing the slope angle, and the chaotic attractor suddenly disappears at a critical slope angle. These make it further difficult to produce stable walking. In our previous work, we used the simplest walking model and investigated the fractal-like basin of attraction based on dynamical systems theory by focusing on the hybrid dynamics of the model composed of the continuous dynamics with saddle hyperbolicity and the discontinuous dynamics by the impact at foot contact. We elucidated that the fractal-like basin of attraction is generated through iterative stretch and bending deformations of the domain of the Poincaré map by sequential inverse images of the Poincaré map. In this study, we investigated the mechanism for the disappearance of the chaotic attractor by improving our previous analysis. In particular, we focused on the range of the Poincaré map to specify the regions to be stretched and bent by the inverse image of the Poincaré map. We clarified the condition for the chaotic attractor to disappear and the mechanism why the chaotic attractor disappears based on the stretch-bending deformation in the basin of attraction.

The observation of quadruped animals has suggested that the body flexibility is important for the bounding gait. In particular, the body flexibility is assumed to be crucial for determining the ground reaction force (GRF). In this paper, we investigated the dynamic effect of the body flexibility on the GRF in quadruped bounding with simple physical models by focusing on the vertical motion. More specifically, we first showed that the body flexibility reduces the GRF using a simple two legged model in sagittal plane. Next, to clarify the GRF reduction mechanism, we further simplified the model, which has only one leg. This allowed us to analytically obtain periodic solutions. Based on the solutions, we investigated the mechanism that the body flexibility reduces the GRF during quadrupedal bounding.

Humans and animals control their walking rhythms to maintain motion in a variable environment. The neural mechanism for controlling rhythm has been investigated in many studies using mechanical and electrical stimulation. However, quantitative evaluation of rhythm variation in response to perturbation at various timings has rarely been investigated. Such a characteristic of rhythm is described by the phase response curve (PRC). Dynamical simulations of human skeletal models with changing walking rhythms (phase reset) described a relation between the effective phase reset on stability and PRC, and phase reset around touch-down was shown to improve stability. A PRC of human walking was estimated by pulling the swing leg, but such perturbations hardly influenced the stance leg, so the relation between the PRC and walking events was difficult to discuss. This research thus examines human response to variations in floor velocity. Such perturbation yields another problem, in that the swing leg is indirectly (and weakly) perturbed, so the precision of PRC decreases. To solve this problem, this research adopts the weighted spike-triggered average (WSTA) method. In the WSTA method, a sequential pulsed perturbation is used for stimulation. This is in contrast with the conventional impulse method, which applies an intermittent impulsive perturbation. The WSTA method can be used to analyze responses to a large number of perturbations for each sequence. In the experiment, perturbations are applied to walking subjects by rapidly accelerating and decelerating a treadmill belt, and measured data are analyzed by the WSTA and impulse methods. The PRC obtained by the WSTA method had clear and stable waveforms with a higher temporal resolution than those obtained by the impulse method. By investigation of the rhythm transition for each phase of walking using the obtained PRC, a rhythm change that extends the touch-down and mid-single support phases is found to occur.

It is important to understand the mechanism of human standing-up motion to improve the declined physical ability of the elderly people. This study employs the concept of muscle synergies (modular structure of coordinative muscle activation) to understand how humans coordinate their muscles to achieve the standing-up motion. Neuro-musculoskeletal model was developed to represent human body to generate standing-up motion. Using the developed model, forward dynamic simulation was used to analyze how humans utilized the muscle synergies to realize the motion. Results showed that the developed model could generate the standing-up motion with four muscle synergies rather than controlling individual muscles. Moreover, further analysis showed that three different strategies of the standing-up motion could be generated only by changing the start time of the particular muscle synergy.

The standing-up motion is one of the most important activities of daily livings. In order to understand the strategy to achieve the standing-up motion, muscle synergy analysis is applied to the measured data during human standing-up motion. In addition, musculoskeletal model which consists of three body segments and nine muscles in lower limb is developed to ensure that the standing-up motion can be generated by muscle synergies. As a result, three muscle synergies have been extracted from the human standing-up motion, and each synergy strongly corresponded to characteristic kinematic events: momentum flexion, momentum transfer, and posture stabilization. Results of forward dynamic simulation show that the standing-up motion can be achieved by controlling time-varying weighting coefficient of three muscle synergies instead of controlling individual nine muscles.

In this paper, we proposed a control system with learning to investigate neuromechanical functions for generating adaptive bipedal locomotion on a splitbelt treadmill. Humans show two types of adaptations, called early adaptation and late adaptation, in splitbelt treadmill walking. In our previous work, we investigated the locomotor behavior of a biped robot driven by nonlinear oscillators with phase resetting and showed that it produced the early adaptation like humans. However, because the locomotion control system did not contain any learning mechanism, it did not show the late adaptation. In this paper, we newly develop learning systems, which modulate the interlimb and intralimb coordination patterns, and incorporate them to our locomotion control system. We investigated the locomotor behavior of a biped robot using computer simulations and robot experiments. The results showed the early and late adaptations during the splitbelt treadmill walking and the time evolution of locomotion parameters was similar to that of humans, which might contribute to understanding of adaptive mechanism in humans and to guiding principle for designing a control system of biped robots.

In this paper, we investigated the dynamics of a hexapod robot model whose legs are driven by nonlinear oscillators with a phase modulation mechanism including phase resetting and inhibition. This mechanism changes the oscillation period of the oscillator depending solely on the timing of the foot's contact. This strategy is based on observation of animals. The performance of the controller is evaluated using a physical simulation environment. Our simulation results show that the robot produces some stable gaits depending on the locomotion speed due to the phase modulation mechanism, which are simillar to the gaits of insects.

Stable locomotion indicates a stable limit cycle generated in the dynamic system. Although quadrupedal bound gait models have been investigated, there is no research which shows the generation of limit cycle and its dynamic properties. In the present study, we analyze a quadrupedal bound gait model which goes down slope and has back and front bodies with spring-damper joint between the bodies. We found the periodic bound gait which achieves a stable limit cycle and convergence property against perturbations.

Although physiological studies have shown evidence of phase resetting during fictive locomotion, the functional roles of phase resetting in actual locomotion remain largely unclear. In this paper, we have constructed a control system for a biped robot based on physiological findings and investigated the functional roles of phase resetting in the gait transition from quadrupedal to bipedal locomotion by numerical simulations and experiments. So far, although many studies have investigated methods to achieve stable locomotor behaviors for various gait patterns of legged robots, their transitions have not been thoroughly examined. Especially, the gait transition from quadrupedal to bipedal requires drastic changes in the robot posture and the reduction of the number of supporting limbs, and therefore, the stability greatly changes during the transition. Thus, this transition poses a challenging task. We constructed a locomotion control system using an oscillator network model based on a two-layer hierarchical network model of a central pattern generator while incorporating the phase resetting mechanism and created robot motions for the gait transition based on the physiological concept of synergies. Our results, which demonstrate that phase resetting increases the robustness in gait transition, will contribute to the understanding of the phase resetting mechanism in biological systems and lead to a guiding principle to design control systems for legged robots.

In this paper, we present an experimental validation of a novel decentralized passivity-based control strategy for teleoperating a group of Unmanned Aerial Vehicles (UAVs): the slave side, consisting of the UAVs, is endowed with large group autonomy by allowing time-varying topology and interrobot/obstacle collision avoidance. The master side, represented by a human operator, controls the group motion and receives suitable force feedback cues informing her/him about the remote slave motion status. Passivity theory is exploited for guaranteeing stability of the slave side and of the overall teleoperation channel. Results of experiments involving the use of 4 quadcopters are reported and discussed, confirming the soundness of the paper theoretical claims.

In this paper, we investigate the locomotor behaviors of a biped robot on a splitbelt treadmill using a locomotion-control system composed of nonlinear oscillators with phase resetting. Our results show that the robot establishes stable walking on the treadmill at various speeds of the belts due to modulation of the rhythm and phase by phase resetting. In addition, the phase differences between the leg movements shifted from out of phase, and duty factors were autonomously modulated depending on the speed discrepancy between the belts occurring through dynamic interactions among the robot's mechanical system, the oscillator control system, and the environment. Such shifts of phase differences between the leg movements and modulations of duty factors are observed during human splitbelt treadmill walking, and our results suggest that our dynamic model using the robot and oscillator control system reflects a certain essence of the ability to produce adaptive locomotor behaviors.

In this paper, we investigated the locomotion of a quadruped robot whose front and rear bodies are connected by a roll joint. The legs of the robot are controlled by nonlinear oscillators with phase resetting. Based on numerical simulations, we showed that the robot produces various gait patterns through dynamical interactions among the robot mechanical system, oscillator control system, and environment and establishes gait transition induced by the change of the roll joint stiffness. In addition, we demonstrated that a hysteresis with respect to gait pattern occurs during the gait transition similarly to humans and animals, and we examined the mechanisms of the hysteresis from a dynamic viewpoint.

This paper addresses the control of the gait change from quadrupedal to bipedal locomotion of a biped robot. In our previous work, we developed a locomotion control system using nonlinear oscillators that generate adaptive walking behavior verified by numerical simulations and hardware experiments. We extended it to deal with the gait change from quadrupedal to bipedal by designing kinematic coordination between these gait patterns, which was only verified by numerical simulations. In this paper, we create a biped robot and improve the control system to verify the performance of the proposed control system.

Simple models with circular arc feet rigidly mounted to the shank of the leg are widely used to investigate bipedal walking behavior. We use a simple walking model with arc feet, whose swing leg is driven by a rhythmic signal from an internal oscillator. The dynamical effects of the arc feet resemble flat feet mounted on ankles with a torsional spring, where the circular arc radius of the arc feet has similar dynamical characteristics to the spring stiffness in the ankle torque. Walking behavior generally consists of the falling motion of the body relative to the stance and the swinging motion of the swing leg. However, when the circular radius exceeds a certain threshold, the body motion changes from such divergent behavior to oscillatory behavior due to the dynamical influence inherent in the arc feet, and the mechanism to create walking behavior greatly changes. Since our model is driven by a rhythmic signal from the oscillator, the walking behavior is driven by two different oscillatory elements and the relationship between them plays an important role. In this paper, we clarify the dynamical effect of the relationship on walking stability.

The motion of the lower limbs in bipedal walking is characterized by a foot-rolling motion, including heel-strike and toe-off. In this paper, the dynamical influence of this motion on walking stability is examined using a simple walking model driven by a rhythmic signal from an internal oscillator. In order to model the rolling motion, a circular arc is attached to the tip of the legs. In particular, we obtained approximate periodic solutions and analyzed the dependence of the local stability on the circular arc radius using a Poincare map, which revealed that the circular arc radius is optimal when it is similar in size to the leg length, to maximize the stable region for such characteristic parameters as mass ratio and walking speed. On the other hand, it is also found that a circular arc radius of zero maximizes the rate of convergence to the stable walking motion. These conflicting results imply that the optimal radius of a circular arc with respect to local stability exists from a trade-off between these different criteria, which should be considered in designing a biped robot.

This paper deals with the walking motion of a biped robot based on a simple model driven by a rhythmic signal from an oscillator. We propose a feedback controller that intermittently modulates the rhythmic signal by using touch sensor signals. We analytically examine the dynamic properties and the performance of the feedback controller based on an approximate analysis using a Poincare map. The analytical results reveal that although the feedback controller doesn't change the stability region, it does improve the stability of the walking motion

This paper deals with the motion of a multi-legged modular robot. The robot consists of six homogenous modules, each of which has a body and two legs and is connected to the others through a three-degree-of-freedom joint. The leg joints are manipulated to follow periodic desired trajectories, and the joints between the modules act like a passive spring with a damper. This robot has characteristic dynamic properties. Specifically, a straight walk naturally turns into a meandering walk by changing the compliance of the joints between the modules without incorporation of any oscillatory inputs. We first show that this transition is excited due to a Hopf bifurcation, based on a numerical simulation and Floquet analysis. Following that, we examine whether the maneuverability and agility increase by utilizing the dynamic characteristics inherent in the robot. In particular, we conduct an experiment in which the robot pursues a target moving across the floor. We propose a simple controller to accomplish the task and achieve high maneuverability and agility by making the most of the robot's dynamic features

This paper deals with the analytical examination of the dynamic properties of the walking motion of a biped robot based on a simple model. The robot is driven by rhythmic signals from an oscillator, which receives feedback signals from touch sensors at the tips of the legs. Instantly, the oscillator resets its phase and modifies the walking motion according to the feedback signals. Based on such a simple model, approximate periodic solutions are obtained, and the stability of the walking motion is analytically investigated by using a Poincare/spl acute/ map. The analytical results demonstrate that the modification of the step period and the walking motion due to the sensory feedback signals improves the stability of the walking motion.

This paper deals with gait transition from quadrupedal to bipedal locomotion of a biped robot. The robot is controlled by our developed locomotion control system composed of nonlinear oscillators, and gait transition is achieved by changing parameters in the control system according to outer commands. Numerical simulations verified that the proposed control system obtains smooth gait transition from quadrupedal to bipedal locomotion.

In our previous work, we developed a locomotion control system of a biped robot which is composed of nonlinear oscillators and realized a stable straight walk of the biped robot against the changes of the environments. Then, we revealed that the adaptability to the changes of the environments is realized as the straight walk results in the change of the period of the motions of the legs. In this paper, we realize a turning walk of the biped robot by using the developed locomotion control system. First, we provide analysis of the turning behavior of the biped robot and reveal that, in this case, the turning behavior leads to the change of the duty ratios of the legs. Moreover, we realize the task that the robot pursues a target on the floor moving along a corner and it demonstrates that the robot can turn a corner successfully in the real world.

This research project, as a part of special project for earthquake disaster mitigation in urban areas initiated by the MEXT, aims to extend the existing robotics and human interface technologies and to establish a novel human-machine interacting structure to enable effective use of semi-autonomous robots in place of humans for searching survivors from rubble under human remote instructions. Collaboration and coordination of the human and robot intelligence and skills are to be developed from both hardware and software viewpoints to make the results of this project contribute to improvement of the search technology, an important issue in the urban robot-assisted search and rescue activities. Research efforts and results are described in this paper.

Human walk is achieved by the interaction between the dynamics of the human mechanical system and the rhythmic signals of the central pattern generator (CPG). In this paper, we analyze dynamic properties of a simple walking model of a biped robot driven by a rhythmic signal of an oscillator. This model consists of a hip and two legs which are connected at the hip. The swing leg is controlled by the rhythmic signal which is open loop. We analyze the stability of the periodic walking motion using a Poincare map. As a result, it is revealed that the simple walking model has the self-stabilization property, that is, the walking motion of the simple walking model converges to a periodic walking motion.

This paper proposes the locomotion control system for a biped locomotion robot. The propose control system is composed of motion generator system and motion control system. Motion generator system is composed of nonlinear oscillators, which generate the commanded trajectories of the joints as functions of phases of oscillators. Motion control system is composed of motors with controllers installed at joints, which control motions of joints. The oscillators tune the phases through the mutual interactions and the feedback signals from the touch sensors at the tips of the legs. As a result, the robot with the controller walks stably by changing its period of locomotion in a changing environment. The performance of the proposed control system is verified by numerical simulations and experiments.