Quadrupeds have versatile gait patterns, depending on the locomotion speed, environmental conditions and animal species. These locomotor patterns are generated via the coordination between limbs and are partly controlled by an intraspinal neural network called the central pattern generator (CPG). Although this forms the basis for current control paradigms of interlimb coordination, the mechanism responsible for interlimb coordination remains elusive. By using a minimalistic approach, we have developed a simple-structured quadruped robot, with the help of which we propose an unconventional CPG model that consists of four decoupled oscillators with only local force feedback in each leg. Our robot exhibits good adaptability to changes in weight distribution and walking speed simply by responding to local feedback, and it can mimic the walking patterns of actual quadrupeds. Our proposed CPG-based control method suggests that physical interaction between legs during movements is essential for interlimb coordination in quadruped walking.

The manner in which quadrupeds change their locomotive patterns—walking, trotting, and galloping—with changing speed is poorly understood. In this paper, we provide evidence for interlimb coordination during gait transitions using a quadruped robot for which coordination between the legs can be self-organized through a simple “central pattern generator” (CPG) model. We demonstrate spontaneous gait transitions between energy-efficient patterns by changing only the parameter related to speed. Interlimb coordination was achieved with the use of local load sensing only without any preprogrammed patterns. Our model exploits physical communication through the body, suggesting that knowledge of physical communication is required to understand the leg coordination mechanism in legged animals and to establish design principles for legged robots that can reproduce flexible and efficient locomotion.

Insects exhibit adaptive and versatile locomotion despite their minimal neural computing. Such locomotor patterns are generated via coordination between leg movements, i.e., an interlimb coordination, which is largely controlled in a distributed manner by neural circuits located in thoracic ganglia. However, the mechanism responsible for the interlimb coordination still remains elusive. Understanding this mechanism will help us to elucidate the fundamental control principle of animals' agile locomotion and to realize robots with legs that are truly adaptive and could not be developed solely by conventional control theories. This study aims at providing a “minimal" model of the interlimb coordination mechanism underlying hexapedal locomotion, in the hope that a single control principle could satisfactorily reproduce various aspects of insect locomotion. To this end, we introduce a novel concept we named “Tegotae,” a Japanese concept describing the extent to which a perceived reaction matches an expectation. By using the Tegotae-based approach, we show that a surprisingly systematic design of local sensory feedback mechanisms essential for the interlimb coordination can be realized. We also use a hexapod robot we developed to show that our mathematical model of the interlimb coordination mechanism satisfactorily reproduces various insects' gait patterns.

Recently, myriapods have attracted the attention of engineers because mobile robots that mimic them potentially have the capability of producing highly stable, adaptive, and resilient behaviors. The major challenge here is to develop a control scheme that can coordinate their numerous legs in real time, and an autonomous decentralized control could be the key to solve this problem. Therefore, we focus on real centipedes and aim to design a decentralized control scheme for myriapod robots by drawing inspiration from behavioral experiments on centipede locomotion under unusual conditions. In the behavioral experiments, we observed the response to the removal of a part of the terrain and to amputation of several legs. Further, we determined that the ground reaction force is significant for generating rhythmic leg movements; the motion of each leg is likely affected by a sensory input from its neighboring legs. Thus, we constructed a two-dimensional model wherein a simple local reflexive mechanism was implemented in each leg. We performed simulations by using this model and demonstrated that the myriapod robot could move adaptively to changes in the environment and body properties. Our findings will shed new light on designing adaptive and resilient myriapod robots that can function under various circumstances.

Legged animals exhibit adaptive and resilient locomotion through interlimb coordination. The long-term goal of this study is to clarify the relationship between the number of legs and the inherent decentralized control mechanism for interlimb coordination. As a preliminary step, the study focuses on millipedes as they represent the species with the greatest number of legs among various animal species. A decentralized control mechanism involving local force feedback was proposed based on the qualitative findings of behavioural experiments in which responses to the removal of part of the terrain and leg amputation were observed. The proposed mechanism was implemented in a developed millipede-like robot to demonstrate that the robot can adapt to the removal of the part of the terrain and leg amputation in a manner similar to that in behavioural experiments.

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