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.     

Modelisation of an unspecialized quadruped walking mammal.

Kinematics and structural analyses were used as basic data to elaborate a dynamic quadruped model that may represent an unspecialized mammal. Hedgehogs were filmed on a treadmill with a cinefluorographic system providing trajectories of skeletal elements during locomotion. Body parameters such as limb segments mass and length, and segments centre of mass were checked from cadavers. These biological parameters were compiled in order to build a virtual quadruped robot. The robot locomotor behaviour was compared with the actual hedgehog to improve the model and to disclose the necessary changes. Apart from use in robotics, the resulting model may be useful to simulate the locomotion of extinct mammals.     

Bio-inspired grasp control in a robotic hand with massive sensorial input

The capability of grasping and lifting an object in a suitable, stable and controlled way is an outstanding feature for a robot, and thus far, one of the major problems to be solved in robotics. No robotic tools able to perform an advanced control of the grasp as, for instance, the human hand does, have been demonstrated to date. Due to its capital importance in science and in many applications, namely from biomedics to manufacturing, the issue has been matter of deep scientific investigations in both the field of neurophysiology and robotics. While the former is contributing with a profound understanding of the dynamics of real-time control of the slippage and grasp force in the human hand, the latter tries more and more to reproduce, or take inspiration by, the nature’s approach, by means of hardware and software technology. On this regard, one of the major constraints robotics has to overcome is the real-time processing of a large amounts of data generated by the tactile sensors while grasping, which poses serious problems to the available computational power. In this paper a bio-inspired approach to tactile data processing has been followed in order to design and test a hardware–software robotic architecture that works on the parallel processing of a large amount of tactile sensing signals. The working principle of the architecture bases on the cellular nonlinear/neural network (CNN) paradigm, while using both hand shape and spatial–temporal features obtained from an array of microfabricated force sensors, in order to control the sensory-motor coordination of the robotic system. Prototypical grasping tasks were selected to measure the system performances applied to a computer-interfaced robotic hand. Successful grasps of several objects, completely unknown to the robot, e.g. soft and deformable objects like plastic bottles, soft balls, and Japanese tofu, have been demonstrated.     

Biorobotic approaches to the study of motor systems

Biorobotics is a promising new area of research at the interface between biology and robotics. Robots can either be used as physical models of biological systems or be directly inspired by biological studies. A great deal of progress has recently been made in biorobotic studies of locomotion, orientation, and vertebrate arm control.     

Modeling locomotion of a soft-bodied arthropod using inverse dynamics

Most bio-inspired robots have been based on animals with jointed, stiff skeletons. There is now an increasing interest in mimicking the robust performance of animals in natural environments by incorporating compliant materials into the locomotory system. However, the mechanics of moving, highly conformable structures are particularly difficult to predict. This paper proposes a planar, extensible-link model for the soft-bodied tobacco hornworm caterpillar, Manduca sexta, to provide insight for biologists and engineers studying locomotion by highly deformable animals and caterpillar-like robots. Using inverse dynamics to process experimentally acquired point-tracking data, ground reaction forces and internal forces were determined for a crawling caterpillar. Computed ground reaction forces were compared to experimental data to validate the model. The results show that a system of linked extendable joints can faithfully describe the general form and magnitude of the contact forces produced by a crawling caterpillar. Furthermore, the model can be used to compute internal forces that cannot be measured experimentally. It is predicted that between different body segments in stance phase the body is mostly kept in tension and that compression only occurs during the swing phase when the prolegs release their grip. This finding supports a recently proposed mechanism for locomotion by soft animals in which the substrate transfers compressive forces from one part of the body to another (the environmental skeleton) thereby minimizing the need for hydrostatic stiffening. The model also provides a new means to characterize and test control strategies used in caterpillar crawling and soft robot locomotion.     

Bio-Inspired Controller for a Robot Cheetah with a Neural Mechanism Controlling Leg Muscles

The realization of a high-speed running robot is one of the most challenging problems in developing legged robots.The excellent performance of cheetahs provides inspiration for the control and mechanical design of such robots.This paper presents a three-dimensional model of a cheetah that predicts the locomotory behaviors of a running cheetah.Applying biological knowledge of the neural mechanism,we control the muscle flexion and extension during the stance phase,and control the positions of the joints in the flight phase via a PD controller to minimize complexity.The proposed control strategy is shown to achieve similar locomotion of a real cheetah.The simulation realizes good biological properties,such as the leg retraction,ground reaction force,and spring-like leg behavior.The stable bounding results show the promise of the controller in high-speed locomotion.The model can reach 2.7 m·s- 1 as the highest speed,and can accelerate from 0 to 1.5 m·s -1 in one stride cycle.A mechanical structure based on this simulation is designed to demonstrate the control approach,and the most recently developed hindlimb controlled by the proposed controller is presented in swinging-leg experiments and jump-force experiments.     

Bipedal locomotion: toward unified concepts in robotics and neuroscience

This review is the result of a joint reflection carried out by researchers in the fields of robotics and automatic control on the one hand and neuroscience on the other, both trying to answer the same question: what are the functional bases of bipedal locomotion and how can they be controlled? The originality of this work is to synthesize the two approaches in order to take advantage of the knowledge concerning the adaptability and reactivity performances of humans and of the rich tools and formal concepts available in biped robotics. Indeed, we claim that the theoretical framework of robotics can enhance our understanding of human postural control by formally expressing the experimental concepts used in neuroscience. Conversely, biological knowledge of human posture and gait can inspire biped robot design and control. Therefore, both neuroscientists and roboticists should find useful information in this paper.     

Effects of body size and shape on locomotion in the bat star (Patiria miniata)

Among taxa ranging from cnidarians to vertebrates, absolute speed of locomotion generally increases with increasing body size. Despite the unique mode of locomotion in echinoderms, crawling speed also appears to increase with increasing body size, at least in some species of asteroids and echinoids. We used an escape-response assay to assess how maximum crawling speed varied with body size in the bat star Patiria miniata. We also tested the effect of arm number on maximum crawling speed by comparing speeds of five- and six-armed individuals. Contrary to prior reports for a single sea urchin and sea star species, both absolute crawling speed and crawling speed relative to body size actually declined with increasing body mass, increasing arm length, and increasing oral surface area, in both five- and six-armed individuals. Arm number did not appear to have a significant effect on crawling speed. The reasons for this negative relationship between crawling speed and body size in P. miniata remain unclear, but we suspect that the disproportionate increase in body mass relative to total tube-foot cross-sectional area may make locomotion proportionally more difficult in larger-bodied sea stars.     

Running over unknown rough terrain with a one-legged planar robot

The ability to traverse unknown, rough terrain is an advantage that legged locomoters have over their wheeled counterparts. However, due to the complexity of multi-legged systems, research in legged robotics has not yet been able to reproduce the agility found in the animal kingdom. In an effort to reduce the complexity of the problem, researchers have developed single-legged models to gain insight into the fundamental dynamics of legged running. Inspired by studies of animal locomotion, researchers have proposed numerous control strategies to achieve stable, one-legged running over unknown, rough terrain. One such control strategy incorporates energy variations into the system during the stance phase by changing the force-free leg length as a sinusoidal function of time. In this research, a one-legged planar robot capable of implementing this and other state-of-the-art control strategies was designed and built. Both simulated and experimental results were used to determine and compare the stability of the proposed controllers as the robot was subjected to unknown drop and raised step perturbations equal to 25% of the nominal leg length. This study illustrates the relative advantages of utilizing a minimal-sensing, active energy removal control scheme to stabilize running over rough terrain.     

Initial Development of a Novel Amphibious Robot with Transformable Fin-Leg Composite Propulsion Mechanisms

Amphibious robots are very attractive for their broad applications in resource exploration, disaster rescue, and recon- naissance. However, it is very challenging to develop the robots for their complex, amphibious working environments. In the complex amphibious environment, amphibious robots should possess multi-capabilities to walk on rough ground, maneuver underwater, and pass through transitional zones such as sandy and muddy terrain. These capabilities require a high-performance propulsion mechanism for the robots. To tackle a complex task, a novel amphibious robot （AmphiHex-I） with,transformable fin-leg composite propulsion mechanisms is developed. With the fin-leg composite propulsions, AmphiHex-I can walk on rough and soft substrates and swim in water with many maneuvers. This paper presents the structural design of the transformable fin-leg propulsion mechanism and its driving module. A hybrid model is used to explore the dynamics between the trans- formable legs and transitional environment such as granular medium. The locomotion performances of legs with various ellip- tical shapes are analyzed, which is verified by the coincidence between the model predictions and the simulation results. Further, an orthogonal experiment is conducted to study the locomotion performance of a two-legged platform walking with an asyn- chronous gait in the sandy and muddy terrain. Finally, initial experiments of AmphiHex-I walking on various lands and swimming in water are implemented. These results verify that the transformable fin-leg mechanisms enable the amphibious robot to pass through a complex, amphibious working environment.     

Sensorimotor control of navigation in arthropod and artificial systems

Arthropods exhibit highly efficient solutions to sensorimotor navigation problems. They thus provide a source of inspiration and ideas to robotics researchers. At the same time, attempting to re-engineer these mechanisms in robot hardware and software provides useful insights into how the natural systems might work. This paper reviews three examples of arthropod sensorimotor control systems that have been implemented and tested on robots. First we discuss visual control mechanisms of flies, such as the optomotor reflex and collision avoidance, that have been replicated in analog VLSI (very large scale integration) hardware and used to produce corrective behavior in robot vehicles. Then, we present a robot model of auditory localization in the cricket; and discuss integration of this behavior with the optomotor behavior previously described. Finally we present a model of olfactory search in the moth, which makes use of several sensory cues, and has also been tested using robot hardware. We discuss some of the similarities and differences of the solutions obtained.     

Biomimetic Motion Control System Based on a CPG for an Amphibious Multi-Link Mobile Robot

Robots and robotics technologies are expected to provide new tools for inspection and manipulation, especially in extreme environments that are dangerous for human beings to access directly, such as underwater environments, volcanic areas, or nuclear power plants. Robots designed for such extreme environments should be sufficiently robust and strong to cope with disturbance and breakdowns. We focus on the movement of animals to realize robust robot systems. One approach is to mimic the nervous systems of animals. The central pattern generator of a nervous system has been shown to control motion patterns, such as walking, respiration and flapping. In this paper, a robot motion control system using a central pattern generator is proposed and applied to an amphibious multi-link mobile robot.     

A new bi-axial cantilever beam design for biomechanics force measurements

The demand for measuring forces exerted by animals during locomotion has increased dramatically as biomechanists strive to understand and implement biomechanical control strategies. In particular, multi-axial force transducers are often required to capture animal limb coordination patterns. Most existing force transducers employ strain gages arranged in a Wheatstone bridge on a cantilever beam. Bi-axial measurements require duplicating this arrangement in the transverse direction. In this paper, we reveal a method to embed a Wheatstone bridge inside another to allow bi-axial measurements without additional strain gages or additional second beams. This hybrid configuration resolves two force components from a single bridge circuit and simplifies fabrication for the simultaneous assessment of normal and transverse loads. This design can be implemented with two-dimensional fabrication techniques and can even be used to modify a common full bridge cantilever force transducer. As a demonstration of the new design, we built a simple beam which achieved bi-axial sensing capability that outperformed a conventional half-bridge-per-axis bi-axial strain gage design. We have used this design to measure the ground reaction forces of a crawling caterpillar and a caterpillar-mimicking soft robot. The simplicity and increased sensitivity of this method could facilitate bi-axial force measurements for experimental biologists.     

Biomimetic Design and Optimal Swing of a Hexapod Robot Leg

Biological inspiration has spawned a wealth of solutions to both mechanical design and control schemes in the efforts to develop agile legged machines. This paper presents a compliant leg mechanism for a small six-legged robot, HITCR-ll, based on abstracted anatomy from insect legs. Kinematic structure, relative proportion of leg segment lengths and actuation system were analyzed in consideration of anatomical structure as well as muscle system of insect legs and desired mobility. A spring based passive compliance mechanism inspired by musculoskeletal structures of biological systems was integrated into distal segment of the leg to soften foot impact on touchdown. In addition, an efficient locomotion planner capable of generating natural movements for the legs during swing phase was proposed. The problem of leg swing was formulated as an optimal control procedure that satisfies a series of locomotion task terms while minimizing a biologically-based objective function, which was solved by a Gauss Pseudospectral Method （GPM） based numerical technique. We applied this swing generation algorithm to both a simulation platform and a robot prototype. Results show that the proposed leg structure and swing planner are able to successfully perform effective swing movements on rugged terrains.     

Morphological Evolution of Physical Robots through Model-Free Phenotype Development

Artificial evolution of physical systems is a stochastic optimization method in which physical machines are iteratively adapted to a target function. The key for a meaningful design optimization is the capability to build variations of physical machines through the course of the evolutionary process. The optimization in turn no longer relies on complex physics models that are prone to the reality gap, a mismatch between simulated and real-world behavior. We report model-free development and evaluation of phenotypes in the artificial evolution of physical systems, in which a mother robot autonomously designs and assembles locomotion agents. The locomotion agents are automatically placed in the testing environment and their locomotion behavior is analyzed in the real world. This feedback is used for the design of the next iteration. Through experiments with a total of 500 autonomously built locomotion agents, this article shows diversification of morphology and behavior of physical robots for the improvement of functionality with limited resources.     

Supervisory control theory applied to swarm robotics

Currently, the control software of swarm robotics systems is created by ad hoc development. This makes it hard to deploy these systems in real-world scenarios. In particular, it is difficult to maintain, analyse, or verify the systems. Formal methods can contribute to overcome these problems. However, they usually do not guarantee that the implementation matches the specification, because the system’s control code is typically generated manually. Also, there is cultural resistance to apply formal methods; they may be perceived as an additional step that does not add value to the final product. To address these problems, we propose supervisory control theory for the domain of swarm robotics. The advantages of supervisory control theory, and its associated tools, are a reduction in the amount of ad hoc development, the automatic generation of control code from modelled specifications, proofs of properties over generated control code, and the reusability of formally designed controllers between different robotic platforms. These advantages are demonstrated in four case studies using the e-puck and Kilobot robot platforms. Experiments with up to 600 physical robots are reported, which show that supervisory control theory can be used to formally develop state-of-the-art solutions to a range of problems in swarm robotics.     

The role of feedback in morphological computation with compliant bodies

The generation of robust periodic movements of complex nonlinear robotic systems is inherently difficult, especially, if parts of the robots are compliant. It has previously been proposed that complex nonlinear features of a robot, similarly as in biological organisms, might possibly facilitate its control. This bold hypothesis, commonly referred to as morphological computation, has recently received some theoretical support by Hauser et?al. (Biol Cybern 105:355–370, doi:10.1007/s00422-012-0471-0, 2012). We show in this article that this theoretical support can be extended to cover not only the case of fading memory responses to external signals, but also the essential case of autonomous generation of adaptive periodic patterns, as, e.g., needed for locomotion. The theory predicts that feedback into the morphological computing system is necessary and sufficient for such tasks, for which a fading memory is insufficient. We demonstrate the viability of this theoretical analysis through computer simulations of complex nonlinear mass–spring systems that are trained to generate a large diversity of periodic movements by adapting the weights of a simple linear feedback device. Hence, the results of this article substantially enlarge the theoretically tractable application domain of morphological computation in robotics, and also provide new paradigms for understanding control principles of biological organisms.     

Central pattern generating networks in insect locomotion

Central pattern generators (CPGs) are neural circuits that based on their connectivity can generate rhythmic and patterned output in the absence of rhythmic external inputs. This property makes CPGs crucial elements in the generation of many kinds of rhythmic motor behaviors in insects, such as flying, walking, swimming, or crawling. Arguably representing the most diverse group of animals, insects utilize at least one of these types of locomotion during one stage of their ontogenesis. Insects have been extensively used to study the neural basis of rhythmic motor behaviors, and particularly the structure and operation of CPGs involved in locomotion. Here, we review insect locomotion with regard to flying, walking, and crawling, and we discuss the contribution of central pattern generation to these three forms of locomotion. In each case, we compare and contrast the topology and structure of the CPGs, and we point out how these factors are involved in the generation of the respective motor pattern. We focus on the importance of sensory information for establishing a functional motor output and we indicate behavior‐specific adaptations. Furthermore, we report on the mechanisms underlying coordination between different body parts. Last but not least, by reviewing the state‐of‐the‐art knowledge concerning the role of CPGs in insect locomotion, we endeavor to create a common ground, upon which future research in the field of motor control in insects can build.     

Development of an Anthropomorphic Robotic Arm and Hand for Interactive Humanoids

Humanoid robots are designed and built to mimic human form and movement.Ultimately,they are meant to resemble the size and physical abilities of a human in order to function in human-oriented environments and to work autonomously but to pose no physical threat to humans.Here,a humanoid robot that resembles a human in appearance and movement is built using powerful actuators paired with gear trains,joint mechanisms,and motor drivers that are all encased in a package no larger than that of the human physique.In this paper,we propose the construction of a humanoid-applicable anthropomorphic 7-DoF arm complete with an 8-DoF hand.The novel mechanical design of this humanoid arm makes it sufficiently compact to be compatible with currently available narrating-model humanoids,and to be sufficiently powerful and flexible to be functional; the number of degrees of freedom endowed in this robotic arm is sufficient for executing a wide range of tasks,including dexterous hand movements.The developed humanoid arm and hand are capable of sensing and interpreting incoming external force using the motor in each joint current without conventional torque sensors.The humanoid arm adopts an algorithm to avoid obstacles and the dexterous hand is capable of grasping objects.The developed robotic arm is suitable for use in an interactive humanoid robot.