Development of a Modular Tensegrity Robot Arm Capable of Continuous Bending.

In this study, we present a tensegrity robot arm that can reproduce the features of complex musculoskeletal structures, and can bend like a continuum manipulator. In particular, we propose a design method for an arm-type tensegrity robot that has a long shape in one direction, and can be deformed like a continuum manipulator. This method is based on the idea of utilizing simple and flexible strict tensegrity modules, and connecting them recursively so that they remain strict tensegrity even after being connected. The tensegrity obtained by this method strongly resists compressive forces in the longitudinal direction, but is flexible in the bending direction. Therefore, the changes in stiffness owing to internal forces, such as in musculoskeletal robots, appear more in the bending direction. First, this study describes this design method, then describes a developed pneumatically driven tensegrity robot arm with 20 actuators. Next, the range of motion and stiffness under various driving patterns are presented as evaluations of the robot performance.

Robotic investigation on effect of stretch reflex and crossed inhibitory response on bipedal hopping.

To maintain balance during dynamic locomotion, the effects of proprioceptive sensory feedback control (e.g. reflexive control) should not be ignored because of its simple sensation and fast reaction time. Scientists have identified the pathways of reflexes; however, it is difficult to investigate their effects during locomotion because locomotion is controlled by a complex neural system and current technology does not allow us to change the control pathways in living humans. To understand these effects, we construct a musculoskeletal bipedal robot, which has similar body structure and dynamics to those of a human. By conducting experiments on this robot, we investigate the effects of reflexes (stretch reflex and crossed inhibitory response) on posture during hopping, a simple and representative bouncing gait with complex dynamics. Through over 300 hopping trials, we confirm that both the stretch reflex and crossed response can contribute to reducing the lateral inclination during hopping. These reflexive pathways do not use any prior knowledge of the dynamic information of the body such as its inclination. Beyond improving the understanding of the human neural system, this study provides roboticists with biomimetic ideas for robot locomotion control.

Three-dimensional innate mobility of the human foot bones under axial loading using biplane X-ray fluoroscopy.

The anatomical design of the human foot is considered to facilitate generation of bipedal walking. However, how the morphology and structure of the human foot actually contribute to generation of bipedal walking remains unclear. In the present study, we investigated the three-dimensional kinematics of the foot bones under a weight-bearing condition using cadaver specimens, to characterize the innate mobility of the human foot inherently prescribed in its morphology and structure. Five cadaver feet were axially loaded up to 588 N (60 kgf), and radiographic images were captured using a biplane X-ray fluoroscopy system. The present study demonstrated that the talus is medioinferiorly translated and internally rotated as the calcaneus is everted owing to axial loading, causing internal rotation of the tibia and flattening of the medial longitudinal arch in the foot. Furthermore, as the talus is internally rotated, the talar head moves medially with respect to the navicular, inducing external rotation of the navicular and metatarsals. Under axial loading, the cuboid is everted simultaneously with the calcaneus owing to the osseous locking mechanism in the calcaneocuboid joint. Such detailed descriptions about the innate mobility of the human foot will contribute to clarifying functional adaptation and pathogenic mechanisms of the human foot.

Shoulder complex linkage mechanism for humanlike musculoskeletal robot arms.

The shoulder complex in the human body consists of the scapula, clavicle, humerus, and thorax and bears the load imposed by arm movements while at the same time realizing a wide range of motions. To mimic and exploit its role, several musculoskeletal robot arms with shoulder complex mechanisms have been developed. However, although many research groups have tried to design the structures using links and joints that faithfully correspond to the bones and joints in the human shoulder complex, its function has not been successfully reproduced because biologically plausible designs seriously compromise engineering plausibility. In this paper, we propose a linkage mechanism that can reproduce complex three-dimensional scapulo movements and considers the trade-off between biological and engineering plausibilities. Subsequently, the design was validated by driving the mechanism using pneumatic artificial muscles (PAMs) placed similarly to muscles in humans. Further, we present experiments in which the robot was controlled by surface electromyographic signals from a human. We show that the proposed design, due to its kinematic similarity with human musculoskeletal systems, eases the conversion between the surface electromyogram signals and the PAMs control inputs.

Direct assessment of 3D foot bone kinematics using biplanar X-ray fluoroscopy and an automatic model registration method.

BACKGROUND: Quantifying detailed 3-dimensional (3D) kinematics of the foot in contact with the ground during locomotion is crucial for understanding the biomechanical functions of the complex musculoskeletal structure of the foot. Biplanar X-ray fluoroscopic systems and model-based registration techniques have recently been employed to capture and visualise 3D foot bone movements in vivo, but such techniques have generally been performed manually. In the present study, we developed an automatic model-registration method with biplanar fluoroscopy for accurate measurement of 3D movements of the skeletal foot. METHODS: Three-dimensional surface models of foot bones were generated prior to motion measurement based on computed tomography. The bone models generated were then registered to biplanar fluoroscopic images in a frame-by-frame manner using an optimisation technique, to maximise similarity measures between occluding contours of the bone surface models with edge-enhanced fluoroscopic images, while avoiding mutual penetration of bones. A template-matching method was also introduced to estimate the amount of bone translation and rotation prior to automatic registration. RESULTS: We analysed 3D skeletal movements of a cadaver foot mobilized by a robotic gait simulator. The 3D kinematics of the calcaneus, talus, navicular and cuboid in the stance phase of the gait were successfully reconstructed and quantified using the proposed model-registration method. The accuracy of bone registration was evaluated as 0.27 ± 0.19 mm and 0.24 ± 0.19° (mean ± standard deviation) in translation and rotation, respectively, under static conditions, and 0.36 ± 0.19 mm and 0.42 ± 0.30° in translation and rotation, respectively, under dynamic conditions. CONCLUSIONS: The measurement was confirmed to be sufficiently accurate for actual analysis of foot kinematics. The proposed method may serve as an effective tool for understanding the biomechanical function of the human foot during locomotion.

Robust sensorimotor representation to physical interaction changes in humanoid motion learning.

This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply this knowledge during different physical interactions between a robot and its surroundings. The phase transfer sequence represents the temporal order of the changing points in multiple time sequences. It encodes the dynamical aspects of the sequences so as to absorb the gaps in timing and amplitude derived from interaction changes. The phase transfer sequence was evaluated in reinforcement learning of sitting-up and walking motions conducted by a real humanoid robot and compatible simulator. In both tasks, the robotic motions were less dependent on physical interactions when learned by the proposed feature than by conventional similarity measurements. Phase transfer sequence also enhanced the convergence speed of motion learning. Our proposed feature is original primarily because it absorbs the gaps caused by changes of the originally acquired physical interactions, thereby enhancing the learning speed in subsequent interactions.

Minimalistic behavioral rule derived from bacterial chemotaxis in a stochastic resonance setup.

Animals are able to cope with the noise, uncertainties, and complexity of the real world. Often even elementary living beings, equipped with very limited sensory organs, are able to reach regions favorable to their existence, using simple stochastic policies. In this paper we discuss a minimalistic stochastic behavioral rule, inspired from bacteria chemotaxis, which is able to increase the value of a specified evaluation function in a similar manner. In particular, we prove that, under opportune assumptions, the direction that is taken with maximum probability by an agent that follows this rule corresponds to the optimal direction. The rule does not require a specific agent dynamics, needs no memory for storing observed states, and works in generic n-dimensional spaces. It thus reveals itself interesting for the control of simple sensing robots as well.

Self-protective whole body motion for humanoid robots based on synergy of global reaction and local reflex.

This paper describes a self-protective whole body motor controller to enable life-long learning of humanoid robots. In order to reduce the damages on robots caused by physical interaction such as obstacle collision, we introduce self-protective behaviors based on the adaptive coordination of full-body global reactions and local limb reflexes. Global reactions aim at adaptive whole-body movements to prepare for harmful situations. The system incrementally learns a more effective association of the states and global reactions. Local reflexes based on a force-torque sensing function to reduce the impact load on the limbs independently of high-level motor intention. We examined the proposed method with a robot simulator in various conditions. We then applied the systems on a real humanoid robot.

Stochastic resonance emergence from a minimalistic behavioral rule.

Stochastic resonance (SR) is a phenomenon occurring in nonlinear systems by which the ability to process information, for instance the detection of weak signals is statistically enhanced by a non-zero level of noise. SR effects have been observed in a great variety of systems, comprising electronic circuits, optical devices, chemical reactions and neurons. In this paper we report the SR phenomena occurring in the execution of an extremely simple behavioral rule inspired from bacteria chemotaxis. The phenomena are quantitatively analyzed by using Markov chain models and Monte Carlo simulations.