Robots of today are eager to leave constrained industrial environments and embrace unexplored and unstructured areas, for extensive applications in the real world as service and social robots. Hence, in addition to these new physical frontiers, they must face human ones, too. This implies the need to consider a human-robot interaction from the beginning of the design; the possibility for a robot to recognize users’ emotions and, in a certain way, to properly react and “behave”. This could play a fundamental role in their integration in society. However, this capability is still far from being achieved. Over the past decade, several attempts to implement automata for different applications, outside of the industry, have been pursued. But very few applications have tried to consider the emotional state of users in the behavioural model of the robot, since it raises questions such as: how should human emotions be modelled for a correct representation of their state of mind? Which sensing modalities and which classification methods could be the most feasible to obtain this desired knowl-edge? Furthermore, which applications are the most suitable for the robot to have such sensitivity? In this context, this paper aims to provide a general overview of recent attempts to enable robots to recognize human emotions and interact properly.

Soft robotics has several promising properties for aquatic applications, such as safe interaction with environments, lightweight, low cost, etc. In this paper, we proposed the kinematic modeling and hydrodynamics experiments of a soft robotic arm with 3D locomotion capacity. We developed a mathematical model that incorporates the angle correction, as well as the open-loop model-based motion control. The model could precisely predict the three-dimensional (3D) movement, and the location error is less than 5.7 mm in different attitudes. Furthermore, we performed the hydrodynamic investigations and simultaneously measured the hydrodynamic forces and the wake flows at different amplitudes (50 mm, 100 mm, 150 mm, 200 mm) and frequencies (0.3 Hz, 0.4 Hz, 0.5 Hz) of the soft arm. Surprisingly, we found that the magnitudes of the hydrodynamic force (<1 N) and the torques (<0.08 N•m) of dynamically moving soft arm were tiny, which leads to negligible inertial effect for the underwater vehicle than those of the traditional rigid underwater manipulator. Finally, we dem-onstrated underwater picking and placing tasks of the soft manipulator by using a computer program that controls the tip attitude and velocity. This study may inspire future underwater manipulators that have properties of low-inertial, low power cost and can safely interact with the aquatic environments.

This article presented a four-fingered soft bionic robotic gripper with variable effective actuator lengths. By combining approaches of finite element analysis, quasi-static analytical modeling, and experimental measurements, the deformation of the single soft actuator as a function of air pressure input in free space was analyzed. To investigate the effect of the effective actuator length on the gripping per-formance of the gripper, we conducted systematical experiments to evaluate the pull-off force, the actuation speed, the precision and error tolerance of the soft gripper while grasping objects of various sizes and shapes. A combination of depressurization and pressurization in actuation as well as applying variable effective actuator length enhanced the gripper’s performance significantly, with no sensors. For example, with tunable effective actuator length, the gripper was able to grasp objects ranging from 2 mm – 170 mm robustly. Under the optimal length, the gripper could generate the maximum pull-off force for the corresponding object size; the precision and the error tol-erance of the gripper were also significantly improved compared to those of the gripper with full-length. Our soft robotic prototype ex-hibits a simple control and low-cost approach of gripping a wide range of objects and may have wide leverage for future industrial op-erations.

As the domains, in which robots operate change the objects a robot may be required to grasp and manipulate, are likely to vary sig-nificantly and often. Furthermore there is increasing likelihood that in the future robots will work collaboratively alongside people. There has therefore been interest in the development of biologically inspired robot designs which take inspiration from nature. This paper pre-sents the design and testing of a variable stiffness, three fingered soft gripper, which uses pneumatic muscles to actuate the fingers and granular jamming to vary their stiffness. This gripper is able to adjust its stiffness depending upon how fragile/deformable the object being grasped is. It is also lightweight and low inertia, making it better suited to operation near people. Each finger is formed from a cylindrical rubber bladder filled with a granular material. It is shown how decreasing the pressure inside the finger increases the jamming effect and raises finger stiffness. The paper shows experimentally how the finger stiffness can be increased from 21 N•m−1 to 71 N•m−1. The paper also describes the kinematics of the fingers and demonstrates how they can be position-controlled at a range of different stiffness values.

Upper limb exoskeletal rehabilitation robots are required to assist patients’ arms to perform activities of daily living according to their motion intentions. In this paper, we address two questions: how to design an exoskeletal robot which can mechanically reconstruct func-tional movements using only a few actuators and how to establish wrench-based assistive control. We first show that the mechanism replicating the synergic feature of the human upper limb can be designed in a recursive manner, meaning that the entire robot can be constructed from two basic mechanical units. Next, we illustrate that the assistive control for the synergetic exoskeletal robot can be transformed into an optimization problem and a Riemannian metric is proposed to generate anthropomorphic reaching movements ac-cording to contact forces and torques. Finally, experiments are carried out to verify the functionality of the proposed theory.

Bionic robotic fish has a significant impact on design and control of innovative underwater robots capable of both rapid swimming and high maneuverability. This paper explores the relationship between Central Pattern Generator (CPG) based locomotion control and energy consumption of a miniature self-propelled robotic fish. To this end, a real-time energy measurement system compatible with the CPG-based locomotion control is firstly built on an embedded system. Then, tests are conducted on the untethered actual robot. The results indicate that different CPG feature parameters involving amplitude, frequency, and phase lag play distinct roles in energy consumption under different swimming gaits. Specifically, energy consumption is positively correlated with the changes in the amplitude and frequency of CPGs, whereas the phase lag of CPGs has little influence on the energy consumption. It may offer important inspiration for improving energy efficiency and locomotion performance of versatile swimming gaits.

The applications of robotic fish require high propulsive efficiency mechanism to prolong the mission time. Though many methods were applied, robotic fish still suffers from low efficiency. To improve the efficiency of robotic fish, this paper proposes a variable stiffness mechanism which is based on the negative work. The live fish adjusts its body stiffness to save energy when the muscles do negative work. Inspired by the live fish, a control mechanism based on negative work is proposed to change the stiffness of the robotic fish for higher efficiency. Changing the stiffness of the robotic fish is to change the joint-stiffness. A fuzzy controller is introduced to mimic the variable stiffness mechanism of the fish and depicts the relationship between the stiffness and the negative work. To evaluate the performance of this controller, a two-joint robotic fish model is established based on its kinematic model and hydrodynamic model. The evaluation results show that the robotic fish reduces the energy consumption and improves the propulsion efficiency when introducing the variable stiffness mechanism. Different environments with the control mechanism impact differently on propulsive efficiency. This mechanism may provide a high efficient propulsion control method for the robotic fish.

This paper first analyzed the longitudinal dynamic behavior during vertical takeoff without control of a Flapping-Wing Micro Air Vehicle (FW-MAV). The standard linear flight dynamics based on small disturbances from trim condition was not applicable for our analysis because the initial flight condition, which was at rest on the ground, could be such a large disturbance from the trim condition that the linearization is invalid. Therefore, we derived linearized Equations of Motion (EoM) which can treat an untrimmed flight condition as a reference for disturbances. The Computational Fluid Dynamic (CFD) software ANSYS Fluent was used to compute the aerodynamic forces and pitching moments. Three flight modes were found: a fast subsidence mode, a slow subsidence mode and a divergence oscil-latory mode. Due to divergence oscillatory mode, the deviation from the reference flight grew with time; the FW-MAV tumbled without control. The simulation showed for the first 0.5 second after leaving the ground (the time that is long enough for delay of feedback control), the FW-MAV flew up to a height of 6 cm with small horizontal and pitching motion, which is close to a vertical flight.

The micro Flapping Rotary Wing (FRW) concept inspired by insects was proposed recently. Its aerodynamic performance is highly related to wing pitching and rotational motions. Therefore, the effect of wing pitching kinematics and rotational speed on unsteady aerodynamic forces and power consumption of a FRW in hovering flight is further studied in this paper using computational fluid dy-namics method. Considering a fixed pitching amplitude (i.e., 80?), the vertical force of FRW increases with the downstroke angle of attack and is enhanced by high wing rotational speed. However, a high downstroke angle of attack is not beneficial for acquiring high rotational speed, in which peak vertical force at balance status (i.e., average rotational moment equals zero.) is only acquired at a comparatively small negative downstroke angle of attack. The releasing constraint of pitching amplitude, high rotational speed and enhanced balanced vertical force can be acquired by selecting small pitching amplitude despite high power consumption. To confirm which wing layout is more power efficient for a certain vertical force requirement, the power consumed by FRW is compared with the Rotary Wing (RW) and the Flapping Wing (FW) while considering two angle of attack strategies without the Reynolds number (Re) constraint. FRW and RW are the most power efficient layouts when the target vertical force is produced at an angle of attack that corresponds to the maximum vertical force coefficient and power efficiency, respectively. However, RW is the most power efficient layout overall despite its insufficient vertical force production capability under a certain Re.

This paper presents a novel Central Pattern Generator (CPG) based rolling gait generation in a small-sized spherical robot and its nonlinear control mechanism. A rhythmic rolling pattern mimicking Pleurotya caterpillar is produced for the spherical robot locomotion. A synergetically combined feedforward-feedback control strategy is proposed. The feedforward component is generated from centrally connected network of CPGs in conjunction with nonlinear robot dynamics. Two nonlinear feedback control methods namely integral (first order) Sliding Mode Control (SMC) and High (or second) Order Sliding Mode Control (HOSMC) are proposed to regulate robot stability and gait robustness in the presence of matched parameter uncertainties and bounded external disturbances. Design, implementation and experimental evaluation of both roll gait control strategies for the spherical robot are done on smooth (indoor) and irregular (outdoor) ground surfaces. The performance of robot control is quantified by measuring the roll angle stability, phase plane convergence and wheel velocities. Experimental results show that proposed novel strategy is efficient in producing a stable rolling gait and robust control of a spherical robot on two different types of surfaces. It further shows that proposed high HOSMC strategy is more efficient in robust rolling gait control of a spherical robot compared to an integral first-order SMC on two different ground conditions.

Achieving galloping gait in quadruped robots is challenging, because the galloping gait exhibits complex dynamical behaviors of a hybrid nonlinear under-actuated dynamic system. This paper presents a learning approach to quadruped robot galloping control. The control function is obtained through directly approximating real gait data by learning algorithm, without consideration of robot’s model and environment where the robot is located. Three motion control parameters are chosen to determine the galloping process, and the deduced control function is learned iteratively with modified Locally Weighted Projection Regression (LWPR) algorithm. Experiments conducted upon the bioinspired quadruped robot, AgiDog, indicate that the robot can improve running performance continuously along the learning process, and adapt itself to model and environment uncertainties.

This work concerns biped adaptive walking control on slope terrains with online trajectory generation. In terms of the lack of satis-factory performances of the traditional simplified single-layered Central Pattern Generator (CPG) model in engineering applications where robots face unknown environments and access feedback, this paper presents a Multi-Layered CPG (ML-CPG) model based on a half-center CPG model. The proposed ML-CPG model is used as the underlying low-level controller for a quadruped robot to generate adaptive walking patterns. Rhythm-generation and pattern formation interneurons are modeled to promptly generate motion rhythm and patterns for motion sequence control, while motoneurons are modeled to control the output strength of the joint in real time according to feedback. Referring to the motion control mechanisms of animals, a control structure is built for a quadruped robot. Multi-sensor models abstracted from the neural reflexes of animals are involved in all the layers of neurons through various feedback paths to achieve adaptability as well as the coordinated motion control of a robot’s limbs. The simulation experiments verify the effectiveness of the pre-sented ML-CPG and multi-layered reflexes strategy.

In this paper, a rotational leg-type miniature robot with a bioinspired actuated middle joint and a tail is proposed for stable locomotion and improved climbing ability. The robot has four independently actuated rotational legs, giving it advantages of both wheel-type and leg-type locomotion. The design parameters of the rotational legs were determined by 3D simulation within the seven candidates that selected by a newly proposed metric. It also has unique characteristics inspired by biological structures: a middle joint and a tail. An actuated middle joint allows the frontal body to be lifted or lowered, which was inspired by a flexible body joint of animals, to climb higher obstacles. Effectiveness of the middle joint was analytically verified by the geometric analysis of the robot. Additionally, a multi-functional one Degree Of Freedom (1-DOF) tail was added; the tail prevented the body being easily flipped, while allowed the robot to climb higher obstacles. A bristle-inspired micro structure was attached to the tail to enhance straightness of locomotion. Body size of the robot was 158 mm × 80 mm × 85 mm and weighed 581 g including a 7.4 V Li-Polymer battery. The average velocity of the robot was
2.74 m•s−1 (17.67 body lengths per second) and the maximum height of an obstacle that the robot could climb was 106 mm (2.5 times of leg length), which all were verified by experiments.

Many animals exhibit strong mechanical interlocking in order to achieve efficient climbing against rough surfaces by using their claws in the pads. To maximally use the mechanical interlocking, an innovative robot which utilizes flexible pad with claws is designed. The mechanism for attachments of the claws against rough surfaces is further revealed according to the theoretical analysis. Moreover, the effects of the key parameters on the performances of the climbing robots are obtained. It indicates that decreasing the size of the tip of the claws while maintaining its stiffness unchanged can effectively improve the attachment ability. Furthermore, the structure of robot body and two foot trajectories are proposed and the new robot is presented. Using experimental tests, it demonstrates that this robot has high stability and adaptability while climbing on vertical rough surfaces up to a speed of 4.6 cm•s−1.

Inspired by creatures with membrane to obtain ultra-high gliding ability, this paper presents a robotic flying squirrel (a novel gliding robot) characterized as membrane wing and active membrane deformation. For deep understanding of membrane wing and gliding mechanism from a robotic system perspective, a simplified blocking aerodynamic model of the deformable membrane wing and CFD simulation are finished. In addition, a physical prototype is developed and wind tunnel experiments are carried out. The results show that the proposed membrane wing is able to support the gliding action of the robot. Meanwhile, factors including geometry characteristics, material property and wind speed are considered in the experiments to investigate the aerodynamic effects of the deformable membrane wing deeply. As a typical characteristic of robotic flying squirrel, deformation modes of the membrane wing not only affect the gliding ability, but also directly determine the effects of the posture adjustment. Moreover, different deformation modes of membrane wing are illustrated to explore the possible effects of active membrane deformation on the gliding performance. The results indicate that the de-formation modes have a significant impact on posture adjustment, which reinforces the rationality of flying squirrel’s gliding strategy and provides valuable information on prototype optimal design and control strategy in the actual gliding process.

This paper deals with inverse displacement analysis of a Hyper-redundant Elephant’s Trunk Robot (HRETR). The HRETR is con-nected in series with n modules of 3UPS-PRU parallel mechanism where the underline P denotes an active prismatic joint. Based on the idea of differential geometry, backbone curve of the robot is formulated by using a parametric function consisting of sub-functions and control parameters. A general algorithm for generating a backbone curve and fitting the modules to the backbone curve is proposed. In this way, the inverse displacement analysis of the robot can be carried out by solving the inverse displacement problem of each parallel mechanism module and taking into account the length limits of the links. A HRETR with 6 modules is taken as an example to demonstrate the applicability of the algorithm.