Designing higher fourier harmonics of Tegotae function using genetic algorithm-a case study with an earthworm locomotion

Adaptive and Energy-Efficient Optimal Control in CPGs Through Tegotae-Based Feedback

To obtain biologically inspired robotic control, the architecture of central pattern generators (CPGs) has been extensively adopted to generate periodic patterns for locomotor control. This is attributed to the interesting properties of nonlinear oscillators. Although sensory feedback in CPGs is not necessary for the generation of patterns, it plays a central role in guaranteeing adaptivity to environmental conditions. Nonetheless, its inclusion significantly modifies the dynamics of the CPG architecture, which often leads to bifurcations. For instance, the force feedback can be exploited to derive information regarding the state of the system. In particular, the Tegotae approach can be adopted by coupling proprioceptive information with the state of the oscillation itself in the CPG model. This paper discusses this policy with respect to other types of feedback; it provides higher adaptivity and an optimal energy efficiency for reflex-like actuation. We believe this is the first attempt to analyse the optimal energy efficiency along with the adaptivity of the Tegotae approach.

Tegotae-Based Control Produces Adaptive Inter- and Intra-limb Coordination in Bipedal Walking

Despite the appealing concept of central pattern generator (CPG)-based control for bipedal walking robots, there is currently no systematic methodology for designing a CPG-based controller. To remedy this oversight, we attempted to apply the Tegotae approach, a Japanese concept describing how well a perceived reaction, i.e., sensory information, matches an expectation, i.e., an intended motor command, in designing localised controllers in the CPG-based bipedal walking model. To this end, we developed a Tegotae function that quantifies the Tegotae concept. This function allowed incorporating decentralised controllers into the proposed bipedal walking model systematically. We designed a two-dimensional bipedal walking model using Tegotae functions and subsequently implemented it in simulations to validate the proposed design scheme. We found that our model can walk on both flat and uneven terrains and confirmed that the application of the Tegotae functions in all joint controllers results in excellent adaptability to environmental changes.

Decoding Decentralized Control Mechanism Underlying Adaptive and Versatile Locomotion of Snakes

Snakes have no limbs and can move in various environments using a simple elongated limbless body structure obtained through a long-term evolutionary process. Specifically, snakes have various locomotion patterns, which they change in response to conditions encountered. For example, on an unstructured terrain, snakes actively utilize the terrain's irregularities and move effectively by actively pushing their bodies against the "scaffolds" that they encounter. In a narrow aisle, snakes exhibit concertina locomotion, in which the tail part of the body is pulled forward with the head part anchored, and this is followed by the extension of the head part with the tail part anchored. Furthermore, snakes often exhibit three-dimensional (3-D) locomotion patterns wherein the points of ground contact change in a spatiotemporal manner, such as sidewinding and sinus-lifting locomotion. This ability is achieved possibly by a decentralized control mechanism, which is still mostly unknown. In this study, we address this aspect by employing a synthetic approach to understand locomotion mechanisms by developing mathematical models and robots. We propose a Tegotae-based decentralized control mechanism and use a 2-D snake-like robot to demonstrate that it can exhibit scaffold-based and concertina locomotion. Moreover, we extend the proposed mechanism to 3D and use a 3-D snake-like robot to demonstrate that it can exhibit sidewinding and sinus-lifting locomotion. We believe that our findings will form a basis for developing snake-like robots applicable to search-and-rescue operations as well as understanding the essential decentralized control mechanism underlying animal locomotion.

In-plane gait planning for earthworm-like metameric robots using genetic algorithm

Locomotion of earthworm-like metameric robots results from shape changes of deformable segments. Morphologically, the segments could stretch, contract or bend by changing their states. Periodic shape changes are recognized as gaits of the robots. Robots could employ different gaits for different locomotion tasks. However, earthworm-like robots generally possess a number of independent segments and their hyper-redundant morphology (Chirikjian G S and Burdick J W 1995 IEEE Trans. Robot. Autom. 11 781-93) poses a challenge to gait planning for their locomotion. Hence, the goal of this paper is to establish a framework of in-plane gait planning for earthworm-like robots. To this end, a generic model of earthworm-like robots modelled in our prior work (Zhan X et al 2019 Int. J. Robot. Res. 38 1751-1774) is firstly reviewed and in-plane gaits of the robot are parameterized by adopting the principle of retrograde peristaltic wave (Quillin K J 1999 J. Exp. Biol. 202 661-674). Following this, gaits of earthworm-like robots could be uniquely determined by gait parameters, and gait planning of the robots is then reduced to optimizing the gait parameters. The framework mainly consists of a locomotion simulation module and a genetic algorithm module. In the locomotion simulation, the performance of each gait would be evaluated, and then gait parameters get evolved based on the fitness in the genetic algorithm module. To evaluate the fitness of each gait, two objective functions, i.e., the distance to goals and the number of locomotion steps the earthworm-like robot taken before reaching the goals, are to be minimized in the optimization. Besides, two stopping criteria are proposed to improve the efficiency of evaluation. The framework proposed in the paper could plan in-plane gaits of earthworm-like robots, in contrast, only rectilinear locomotion is considered in similar works. This greatly advances the state of art of earthworm-like robots.