In this article, we demonstrate the value of using decoupled neural oscillators in conjunction with appropriate mechanical designs for snake-like robots engaging in field locomotion. Even though our typical wheeled snake robot with decoupled neural oscillators incorporating angle joint feedback can generate consistent lateral undulation, it lacks robustness. A purely decoupled actuation strategy is not practical for field locomotion. However, the application of one-way wheels and elasticity between the modules improves robustness, allowing our robot to traverse outdoor open terrain. On the other hand, the physical form of the undulatory motion must be varied to pass through intricate narrow-field environments. The lack of neural constraints between the modules passively enables this variability and also facilitates each module independently gaining propulsion (i.e., by means of reflexive thrust via sensory feedback to the neural oscillator and one-way traction generated by one-way side rollers). The designed robot is able to engage in fast creeping motion through an environment containing randomly distributed logs. The results of the field experiments show that the specially designed mechanisms in conjunction with decoupled oscillators can enhance robustness, variability, and independent local propulsion.

Snakes are very unique animals that have distinguished motor function adaptable to the most diverse environments in terrestrial animals regardless of their simple cord-shaped body. Revealing the mechanism underlying this distinct locomotion pattern, which is fundamentally different from walking, is significant not only in biological field but also for applications in engineering field. However, it has been difficult to clarify this adaptive function, emerging from dynamic interaction between body, brain and environment, by previous scientific methodologies based on reductionism, where understanding of the total system is approached by analyzing specific individual elements. In this research, we aim at revealing the mechanisms underlying this adaptability by the use of the constructive methodology, in which biological system models reflecting biological knowledge is used as a tool for analysis of the total system. In this report, we present development of system models, i.e. a dynamics simulator and a robot, constructed based on biological data obtained from dissection, CT-imaging, kinematics measurements and EMG measurements. By constructing mechanical models based on anatomical studies and applying control input designed according to EMG and kinematics measurements into the models, locomotion similar to living snakes was achieved and remaining problems in the models were clarified.

We report on the design and stability analysis of a simple quadruped running controller that can autonomously generate steady running with good energy efficiency and suppress such disturbances as irregularities of terrain. The self-stabilization property of the mechanical system is the inspirational source for our idea. We propose an original Delayed Feedback Control (DFC) approach based on measurements of the stance phase period obtained from contact sensors. Here, the DFC approach will not only stabilize running locomotion around the fixed point, but also result in transition from the stand state to the steady bounding running. Finally, we show several simulation results on different terrain (e.g., flat and step) to characterize the performance of the proposed controller. MPEG footage of simulations can be seen at: http://www.kimura.is.uec.ac.jp/running

In this paper, we employed a conservative spring-loaded two-segment legged model to test the effect of passive dynamics on running stability. By numerical return map studies, we investigated system stability and discovered that passive generation of a large variety of cyclic jumping motion on the legged model is possible. The results of this study indicated that the dynamics of suitable mechanical system could significantly alone improve the stability of legged running and suggest that swing phase dynamics may play an important role in adjustment of forward velocity and apex height. Moreover, we used the spring-loaded two segment legged model as a template to construct a simplified model of our Tekken I quadruped robot on numerical simulation. Using the constructed simulator to investigate the quadruped robot system stability, we proposed a simple control method for quadrupedal bounding and verified its effectiveness. In addition, our studies relating to passive dynamics of quadruped robot might help to understand the reliable stability and remarkable maneuverability on our experimental robot.

We have been trying to induce a quadruped robot to walk with medium walking speed on irregular terrain based on biological concepts. We propose the essential conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical system and the neural system by comparing biological concepts with those essential conditions described in physical terms. PD-controller at joints constructs the virtual spring-damper system as the visco-elasticity model of a muscle. The neural system model consists of a CPG (central pattern generator), reflexes and responses. A CPG generates rhythmic motion for walking. We define a "reflex" as joint torque generation based on sensor information and a "response" as CPG phase modulation through sensory feedback to a CPG. The state of the virtual spring-damper system is switched based on the phase signal of the CPG. CPGs, the motion of the virtual spring-damper system of each leg and the rolling motion of the body are mutually entrained through the rolling motion feedback to CPGs, and can generate adaptive walking. We report our experimental results of dynamic walking on irregular terrain in outdoor environment using a self-contained quadruped robot in order to verify the effectiveness of the designed neuro-mechanical system.

We have induced a quadruped robot to walk with medium walking speed on irregular terrain based on biological concepts. The PD-controller at joints constructs the virtual spring-damper system as the visco-elasticity model of a muscle. The neural system model consists of a CPG (central pattern generator) and reflexes. A CPG receives sensory input and changes the period of its own active phase. The desired angle and P-gain of each joint in the virtual spring-damper system is switched based on the phase signal of the CPG. CPGs, the motion of the virtual spring-damper system of each leg and the rolling motion of the body are mutually entrained through the rolling motion feedback to CPGs, and can generate adaptive walking. We report our experimental results of dynamic walking on terrains of medium degrees of irregularity in order to verify the effectiveness of the designed neuro-mechanical system.

This paper presents a new neural system and mechanical system for quadruped robots with compliant legs, a spring mechanism located at the ankle joint. PD-controller at hip and knee joints constructs the virtual spring-damper system as the visco-elasticity model of a muscle. The neural system model consists of a CPG (Central Pattern Generator) and reflexes. A CPG changes the own active phase based on sensory information. The desired angle and P-gain of each joint in the virtual spring-damper system is switched based on the phase signal of the CPG. The pitching motion of the body is entrained into the CPG as a sensory feedback. Therefore, adaptive running can be generated. Some experimental results of running on terrain of low degrees of irregularity are used to verify the effectiveness of the designed neuro-mechanical system.

We attempt to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model consisting of a central pattern generator (CPG) and reflexes. In this paper, we report on a newly developed quadruped robot, which contains a mechanism designed to make adaptive 3D space walking (pitch, roll and yaw planes) on irregular terrain be performed more simply. In 3D walking, a rolling motion is naturally generated in most gaits. By having the rolling motion be the standard oscillation and making the CPGs of the legs be entrained with a rolling motion, we realized the stabilization of the gait at a constant walking speed, in spite of an unbalanced gravity load between the fore and hind legs. We also realized an autonomous gait transition in changing walking speeds, by utilizing such rolling motion feedback to CPGs, in order to reduce energy consumption. Rolling motion feedback to CPGs contributes to gait stabilization in walking on an irregular terrain as a tonic labyrinthine reflex for rolling. At present stage, the robot succeeded in walking over several 2D irregular terrains by using CPGs, a flexor reflex and tonic labyrinthine reflexes for pitching and rolling.

We are trying to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. In our previous study, we integrated several reflexes into a CPG (central pattern generator) and realized adaptive 2D walking on terrain of medium degree of irregularity. In this paper, in order to make the role of a CPG be clear, we investigate the relation between parameters of a CPG and the mechanical system by simulations and experiments. In addition, we show a newly developed quadruped robot, of which mechanism is designed to make adaptive 3D walking on irregular terrain be realized more simply. At this moment, 3D walking on flat terrain is realized by using a neural system model consisting of CPG and reflexes.

We are trying to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. In this paper, we integrate several reflexes such as stretch reflex, vestibulospinal reflex, and extensor and flexor reflex into CPG (central pattern generator). The success in walking on terrain of medium degree of irregularity with fixed parameters of CPG and reflexes shows that the biologically inspired control proposed in this study has an ability for autonomous adaptation to unknown irregular terrain.

We are trying to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. We integrate several reflexes, such as a stretch reflex, a vestibulospinal reflex, and extensor/flexor reflexes, into a CPG (central pattern generator). The success in walking on terrain of medium degree of irregularity with fixed parameters of CPGs and reflexes shows that the biologically inspired control proposed in this study has an ability for autonomous adaptation to unknown irregular terrain.

We attempt to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model. In the paper, in order to realize walking on irregular terrain, we propose the biologically-inspired control method consisting of four levels, these are: "adaptive control using a muscle stiffness model", "adaptive control based on vestibular sensation", "parameters adjustment based on somatic sensation and reflexes coordination based on vestibular sensation", and "motion switching based on visual information". As results of basic experiments of each level, we show that a robot can walk on a single bump, and walk up and dozen a slope by using such adaptive control method. We also show that the functions as a lower controller in the Drew's physiological model for leg control mechanism based on visual information are satisfied by a CPG characterized by mutual entrainment with a musculo-skeletal system, automatic interpolation, and self stabilization. These findings suggest a simple method for producing autonomous adaptive dynamic walking on terrain of high degree irregularity.