On the applicability of the decentralized control mechanism extracted from the true slime mold: a robotic case study with a serpentine robot

A systematic method for an autonomous decentralized control system is still lacking, despite its appealing concept. In order to alleviate this, we focused on the amoeboid locomotion of the true slime mold, and extracted a design scheme for the decentralized control mechanism that leads to adaptive behavior for the entire system, based on the so-called discrepancy function. In this paper, we intensively investigate the universality of this design scheme by applying it to a different type of locomotion based on a 'synthetic approach'. As a first step, we implement this design scheme to the control of a real physical two-dimensional serpentine robot that exhibits slithering locomotion. The experimental results show that the robot exhibits adaptive behavior and responds to the environmental changes; it is also robust against malfunctions of the body segments due to the local sensory feedback control that is based on the discrepancy function. We expect the results to shed new light on the methodology of autonomous decentralized control systems.     

A decentralized control scheme for an effective coordination of phasic and tonic control in a snake-like robot

Autonomous decentralized control has attracted considerable attention because it enables us to understand the adaptive and versatile locomotion of animals and facilitates the construction of truly intelligent artificial agents. Thus far, we have developed a snake-like robot (HAUBOT I) that is driven by a decentralized control scheme based on a discrepancy function, which incorporates phasic control. In this paper, we investigate a decentralized control scheme in which phasic and tonic control are well coordinated, as an extension of our previous study. To verify the validity of the proposed control scheme, we apply it to a snake-like robot (HAUBOT II) that can adjust both the phase relationship between its body segments and the stiffness at each joint. The results indicate that the proposed control scheme enables the robot to exhibit remarkable real-time adaptability over various frictional and inclined terrains. These findings can potentially enable us to gain a deeper insight into the autonomous decentralized control mechanism underlying the adaptive and resilient locomotion of animals.     

Piezoelectrically Actuated Biomimetic Self-Contained Quadruped Bounding Robot

This paper presents the development of a mesoscale self-contained quadruped mobile robot that employs two pieces ofpiezocomposite actuators for the bounding locomotion.The design of the robot leg is inspired by legged insects and animals,and the biomimetic concept is implemented in the robot in a simplified form,such that each leg of the robot has only one degreeof freedom.The lack of degree of freedom is compensated by a slope of the robot frame relative to the horizontal plane.For theimplementation of the self-contained mobile robot,a small power supply circuit is designed and installed on the robot.Experimentalresults show that the robot can locomote at about 50 mm·s^-1with the circuit on board,which can be considered as asignificant step toward the goal of building an autonomous legged robot actuated by piezoelectric actuators.     

Evolving locomotion for a 12-DOF quadruped robot in simulated environments

We demonstrate the power of evolutionary robotics (ER) by comparing to a more traditional approach its performance and cost on the task of simulated robot locomotion. A novel quadruped robot is introduced, the legs of which – each having three non-coplanar degrees of freedom – are very maneuverable. Using a simplistic control architecture and a physics simulation of the robot, gaits are designed both by hand and using a highly parallel evolutionary algorithm (EA). It is found that the EA produces, in a small fraction of the time that takes to design by hand, gaits that travel at two to four times the speed of the hand-designed one. The flexibility of this approach is demonstrated by applying it across a range of differently configured simulators.     

Slime mold inspired routing protocols for wireless sensor networks

Many biological systems are composed of unreliable components which self-organize effectively into systems that achieve a balance between efficiency and robustness. One such example is the true slime mold Physarum polycephalum which is an amoeba-like organism that seeks and connects food sources and efficiently distributes nutrients throughout its cell body. The distribution of nutrients is accomplished by a self-assembled resource distribution network of small tubes with varying diameter which can evolve with changing environmental conditions without any global control. In this paper, we exploit two different mechanisms of the slime mold??s tubular network formation process via laboratory experiments and mathematical behavior modeling to design two corresponding localized routing protocols for wireless sensor networks (WSNs) that take both efficiency and robustness into account. In the first mechanism of path growth, slime mold explores its immediate surroundings to discover and connect new food sources during its growth cycle. We adapt this mechanism for a path growth routing protocol by treating data sources and sinks as singular potentials to establish routes from the sinks to all the data sources. The second mechanism of path evolution is the temporal evolution of existing tubes through nonlinear feedback in order to distribute nutrients efficiently throughout the organism. Specifically, the diameters of tubes carrying large fluxes of nutrients grow to expand their capacities, and tubes that are not used decline and disappear entirely. We adapt the tube dynamics of the slime mold for a path evolution routing protocol. In our protocol, we identify one key adaptation parameter to adjust the tradeoff between efficiency and robustness of network routes. Through extensive realistic network simulations and ideal closed form or numerical computations, we validate the effectiveness of both protocols, as well as the efficiency and robustness of the resulting network connectivity.     

Gait Study and Pattern Generation of a Starfish-Like Soft Robot with Flexible Rays Actuated by SMAs

This paper presents the design and development of a starfish-like soft robot with flexible rays and the implementation of multi-gait locomotion using Shape Memory Alloy （SMA） actuators. The design principle was inspired by the starfish, which possesses a remarkable symmetrical structure and soft internal skeleton. A soft robot body was constructed by using 3D printing technology. A kinematic model of the SMA spring was built and developed for motion control according to displacement and force requirements. The locomotion inspired from starfish was applied to the implementation of the multi-ray robot through the flexible actuation induced multi-gait movements in various environments. By virtue of the proposed ray control patterns in gait transition, the soft robot was able to cross over an obstacle approximately twice of its body height. Results also showed that the speed of the soft robot was 6.5 times faster on sand than on a clammy rough terrain. These experiments demonstrated that the bionic soft robot with flexible rays actuated by SMAs and multi-gait locomotion in proposed patterns can perform successfully and smoothly in various terrains.     

The protoplasmic flow in the myxomycete plasmodium as revealed by a volumetric analysis

Summary The manner of the locomotion of the slime mold,Physarum polycephalum, was shown graphically using a double-chamber volumeter developed by the author. It enabled him to represent in undulating curves every detail of the way in which the slime mold moves on little by little by availing itself of the difference in transport-volume of the endoplasm produced at each repetition of the back and forth streaming.The curve showing the locomotion of the organism pointed out that more than 4 mm³ of protoplasm is sometimes shifted in a direction in one streaming duration. No close relationship is found between the streaming duration and the transport-volume of protoplasm. The intensity of the flow, which may be defined as the volume of protoplasm transported per unit time, can be obtained from the transport-volume curve through its graphical differentiation.     

Coordination of many oscillators and generation of locomotory patterns

This paper considers a synthesis approach to a decentralized autonomous system in which the functional order of the entire system is generated by cooperative interaction among its subsystems, each of which has the autonomy to control a part of the state of the system, and its application to pattern generators of animal locomotion. First, biological locomotory rhythms and their generators, swimming patterns of aquatic animals and gait patterns of quadrupeds, are reviewed briefly. Then, a design principle for autonomous coordination of many oscillators is proposed. Using these results, we synthesize a swimming pattern generator and a gait pattern generator. Finally, it is shown using computer simulations that the proposed systems generate desirable patterns.     

Deriving neural network controllers from neuro-biological data: implementation of a single-leg stick insect controller

This article presents modular recurrent neural network controllers for single legs of a biomimetic six-legged robot equipped with standard DC motors. Following arguments of Ekeberg et?al. (Arthropod Struct Dev 33:287?C300, 2004), completely decentralized and sensori-driven neuro-controllers were derived from neuro-biological data of stick-insects. Parameters of the controllers were either hand-tuned or optimized by an evolutionary algorithm. Employing identical controller structures, qualitatively similar behaviors were achieved for robot and for stick insect simulations. For a wide range of perturbing conditions, as for instance changing ground height or up- and downhill walking, swing as well as stance control were shown to be robust. Behavioral adaptations, like varying locomotion speeds, could be achieved by changes in neural parameters as well as by a mechanical coupling to the environment. To a large extent the simulated walking behavior matched biological data. For example, this was the case for body support force profiles and swing trajectories under varying ground heights. The results suggest that the single-leg controllers are suitable as modules for hexapod controllers, and they might therefore bridge morphological- and behavioral-based approaches to stick insect locomotion control.     

A Bio-Inspired Hopping Kangaroo Robot with an Active Tail

Inspired by kangaroo＇s locomotion, we report on developing a kangaroo-style hopping robot. Unlike bipeds, quadrupeds, or hexapods which altemate the legs for forward locomotion, the kangaroo uses both legs synchronously and generates the forward locomotion by continuous hopping behavior, and the tail actively balances the unwanted angular momentum generated by the leg motion. In this work, we generate the Center of Mass （CoM） locomotion of the robot based on the reduced-order Rolling Spring Loaded Inverted Pendulum （R-SLIP） model, for matching the dynamic behavior of the empirical robot legs. In order to compensate the possible body pitch variation, the robot is equipped with an active tail for pitch variation compensation, emulating the balance mechanism of a kangaroo. The robot is empirically built, and various design issues and strategies are addressed. Finally, the experimental evaluation is executed to validate the performance of the kangaroo-style robot with hopping locomotion.     

Development of a Biomimetic Quadruped Robot

This paper presents the design and prototype of a small quadruped robot whose walking motion is realized by two piezocomposite actuators. In the design, biomimetic ideas are employed to obtain the agility of motions and sustainability of a heavy load. The design of the robot legs is inspired by the leg configuration of insects, two joints （hip and knee） of the leg enable two basic motions, lifting and stepping. The robot frame is designed to have a slope relative to the horizontal plane, which makes the robot move forward. In addition, the bounding locomotion of quadruped animals is implemented in the robot. Experiments show that the robot can carry an additional load of about 100 g and run with a fairly high velocity. The quadruped prototype can be an important step towards the goal of building an autonomous mobile robot actuated by piezocomposite actuators.     

Humanoid robot Lola: Design and walking control

In this paper we present the humanoid robot LOLA, its mechatronic hardware design, simulation and real-time walking control. The goal of the LOLA-project is to build a machine capable of stable, autonomous, fast and human-like walking. LOLA is characterized by a redundant kinematic configuration with 7-DoF legs, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control. Special emphasis was put on an improved mass distribution of the legs to achieve good dynamic performance. Trajectory generation and control aim at faster, more flexible and robust walking. Center of mass trajectories are calculated in real-time from footstep locations using quadratic programming and spline collocation methods. Stabilizing control uses hybrid position/force control in task space with an inner joint position control loop. Inertial stabilization is achieved by modifying the contact force trajectories.     

Bio-inspired design strategies for central pattern generator control in modular robotics

New findings in the nervous system of invertebrates have shown how a number of features of central pattern generator (CPG) circuits contribute to the generation of robust flexible rhythms. In this paper we consider recently revealed strategies that living CPGs follow to design CPG control paradigms for modular robots. To illustrate them, we divide the task of designing an example CPG for a modular robot into independent problems. We formulate each problem in a general way and provide a bio-inspired solution for each of them: locomotion information coding, individual module control and inter-module coordination. We analyse the stability of the CPG numerically, and then test it on a real robot. We analyse steady state locomotion and recovery after perturbations. In both cases, the robot is able to autonomously find a stable effective locomotion state. Finally, we discuss how these strategies can result in a more general design approach for CPG-based locomotion.     

An Approach for Adaptive Limbless Locomotion Using a CPG-Based Reflex Mechanism

Animals＇ free movement in natural environments has attracted many researchers to explore control methods for bio-inspired robots. This paper presents a novel reflex mechanism based on a Central Pattern Generator （CPG） for adaptive locomotion of limbless robots. First, inspired by the concept of reflex arc, the reflex mechanism is designed on a connectionist CPG model. Since the CPG model inspired by the spinal cord of lampreys is developed at the neuron level, it provides a possible natural solution for sensory reflex integration. Therefore, sensory neurons that bridge the external stimuli and the CPG model, together with the concept of reflex arc, are utilized for designing the sensory reflex mechanism. Then, a border reflex and a body reflex are further developed and applied on the ends and the middle part of a limbless robot, respectively. Finally, a ball hitting scenario and a corridor passing scenario are designed to verify the proposed method. Results of simulations and on-site experiments show the feasibility and effectiveness of the reflex mechanism in realizing fast response and adaptive limbless locomotion.     

The effect of 2,4-dinitrophenol on Dictyostelium discoideum oscillations.

During aggregation the cellular slime mold $\text{Dictyostelium discoideum}$ emits pulses of cAMP about every 5 minutes. Only a small fraction of the aggregating cells produces the pulses autonomously, while most cells synthesize and release the nucleotide in a chain-reaction response to the autonomous signals (1). We report here that 2,4-dinitrophenol, KCN, and caffeine all inhibit the autonomous cAMP oscillations but do not interfere with the triggered response. Because of this, and other data (2), we question current models of the oscillatory synthesis of cAMP.     

Cognition of different length by Physarum polycephalum: Weber's law in an amoeboid organism

A true slime mold, the plasmodium of Physarum polycephalum has the ability to find the shortest route between two points in a labyrinth. To find the shortest route between two points, detection of the difference in lengths can be made from two aspects: the absolute difference between the lengths or the ratio of them. We found that the ratio of two lengths, rather than the absolute difference between the two lengths, was important in discriminating the difference in the two lengths by P. polycephalum. This finding indicates that an amoeboid organism detects differences in stimulus intensity as though it is constrained by Weber's law, suggesting that Weber's law is not reliant on the presence of a neural system and is used widely even in Amoebozoa.     

Cell size in Dictyostelium

Cellular slime mold amoebae have become a model system for the study of cell motility and the cytoskeleton. A basic problem which all cells face that involves the cytoskeleton is how to control their size. The varied ways in which cellular slime mold amoebae change their cell size--by changing the size at which division occurs, by cell fusion, and by control over cytokinesis--are reviewed. A model is presented which attempts to explain how the mechanisms affected in certain cytokinesis mutants in Dictyostelium discoideum known as phg mutants could be involved in control of cell size in the predatory slime mold Dictyostelium caveatum.     

Visually guided gait modifications for stepping over an obstacle: a bio-inspired approach

There is an increasing interest in conceiving robotic systems that are able to move and act in an unstructured and not predefined environment, for which autonomy and adaptability are crucial features. In nature, animals are autonomous biological systems, which often serve as bio-inspiration models, not only for their physical and mechanical properties, but also their control structures that enable adaptability and autonomy—for which learning is (at least) partially responsible. This work proposes a system which seeks to enable a quadruped robot to online learn to detect and to avoid stumbling on an obstacle in its path. The detection relies in a forward internal model that estimates the robot’s perceptive information by exploring the locomotion repetitive nature. The system adapts the locomotion in order to place the robot optimally before attempting to step over the obstacle, avoiding any stumbling. Locomotion adaptation is achieved by changing control parameters of a central pattern generator (CPG)-based locomotion controller. The mechanism learns the necessary alterations to the stride length in order to adapt the locomotion by changing the required CPG parameter. Both learning tasks occur online and together define a sensorimotor map, which enables the robot to learn to step over the obstacle in its path. Simulation results show the feasibility of the proposed approach.     

Behaviour-based modelling of hexapod locomotion: linking biology and technical application

Walking in insects and most six-legged robots requires simultaneous control of up to 18 joints. Moreover, the number of joints that are mechanically coupled via body and ground varies from one moment to the next, and external conditions such as friction, compliance and slope of the substrate are often unpredictable. Thus, walking behaviour requires adaptive, context-dependent control of many degrees of freedom. As a consequence, modelling legged locomotion addresses many aspects of any motor behaviour in general. Based on results from behavioural experiments on arthropods, we describe a kinematic model of hexapod walking: the distributed artificial neural network controller walknet. Conceptually, the model addresses three basic problems in legged locomotion. (I) First, coordination of several legs requires coupling between the step cycles of adjacent legs, optimising synergistic propulsion, but ensuring stability through flexible adjustment to external disturbances. A set of behaviourally derived leg coordination rules can account for decentralised generation of different gaits, and allows stable walking of the insect model as well as of a number of legged robots. (II) Second, a wide range of different leg movements must be possible, e.g. to search for foothold, grasp for objects or groom the body surface. We present a simple neural network controller that can simulate targeted swing trajectories, obstacle avoidance reflexes and cyclic searching-movements. (III) Third, control of mechanically coupled joints of the legs in stance is achieved by exploiting the physical interactions between body, legs and substrate. A local positive displacement feedback, acting on individual leg joints, transforms passive displacement of a joint into active movement, generating synergistic assistance reflexes in all mechanically coupled joints.