Snake-like robots have elongated, snake-like bodies. Because of their long and thin shapes, snake-like robots are expected to play different roles than those occupied by other types of robots. For example, snake-like robots can be used to inspect pipes or search for victims at disaster sites. Many studies have focused on the biomimetics, mechanisms, modeling, analysis, control, navigation, sensing, and localization of snake-like robots, and many efforts have been aimed at their industrialization.

This special issue includes a wide range of research and development results from the fields of robotics and mechatronics for snake-like robots and similar elongated, hyper-redundant robots, such as hyper-redundant manipulators, salamander robots, and other articulated mobile robots.

This study presents an autonomous inspection system for underground pits using an articulated mobile robot. The underground pit is composed of several rooms surrounded by concrete connected to each other by winding pipes. Based on an action list created in advance and environmental maps, the robot autonomously inspects the underground pit by switching between three actions: planar motion, winding pipe passing motion, and image capturing. In planar motion, the robot moves around the room while avoiding obstacles and crosses ditches through distinctive behaviors, switching the allocation of the grounded/ungrounded wheels. In the winding pipe-passing motion, the target path is autonomously generated based on the parameters of the winding pipe. Laboratory and field tests were conducted to demonstrate the effectiveness of the proposed system.

A snake robot can form various shapes by fitting to an arbitrary continuous curve thanks to its numerous degrees of freedom. When traversing an unknown complex environment, a snake robot may need to perform local shape transformation to avoid obstacles or perform specific tasks. In this study, we present a local shape transformation control method for expanding the mobility of a snake robot. The proposed control method lifts a local part of the robot away from the target continuous curve while the leading part and the trailing part shift accordingly to remain fitted to the continuous curve without twisting. The proposed local shape transformation is realized by changing the approximation range on the continuous curve without changing the shape of the continuous curve. Simulations were conducted to evaluate the effectiveness of the local hump-shaped transformation control on various types of continuous curves. We also evaluated the proposed control method by comparing it with other local shape transformation control methods through simulations. Additionally, we propose two examples of applications which are the recovery from a stuck state and recovery from joint failure. Experiments were conducted to verify the effectiveness of the proposed control method.

Snake-like robots can achieve flexible movement by simultaneously actuating multiple joints; however, the challenge of high power consumption by driving numerous servomotors under high-load conditions remains. To address this issue, we propose a mechanism that transforms the rear link of a snake-like robot into a wheel-like configuration, enabling a three-wheeled vehicle mode that provides the same traveling speed and efficiency as a wheeled mobile robots on flat surfaces. First, we detail the method for driving the servomotor to achieve undulating locomotion in the snake-like robot with nonuniform link lengths. Next, we propose a method for smoothly switching between the complex-shaped wheel mode and undulating locomotion. Finally, we conduct experiments to assess the travel efficiency in both the undulating mode and the proposed wheel mode across various road surface conditions. Our results demonstrate that the wheel mode achieves higher travel efficiency than the undulating mode on the smooth floors and asphalt.

This paper proposes a control method for semi-autonomous stair climbing using an articulated mobile robot. Stair-climbing motion is achieved by propagating a single backward wave along the body of the robot. The robot moves forward by shifting a part of the body lifted from the step (the elongating part) from front to back. Semi-autonomous stair climbing is accomplished by automatically determining when to shift the elongating part backward based on the relative position between the step and the robot. Furthermore, we developed an actual robot that can measure the relative position between itself and the environment to climb stairs semi-autonomously. The developed robot is equipped with several short-range sensors on the lower part of its body, which can measure the relative distance between the robot and the stair tread surface. The effectiveness of the proposed control method was verified by simulations using a physics simulator and by experiments with the developed robot.

In this paper, we propose a control method for the snake robot to adapt its body shape to the rope tension while climbing a rope, which is a flexible environment, in response to the joints’ current. The frictional force and the robot joint load vary depending on the amount of rope tension. A large tension may overload the robot joints, but a small tension may cause the robot slip and fall. Therefore, it is important for the robot to be able to change its body shape and adapt appropriately to the tension in rope climbing. In order to achieve this, we focused on the fact that joint loads and motor current values are related and devised a control system to change the robot’s body shape according to the motor current values. The concept is to change the robot’s body shape in order to obtain the maximum twisting angle at a constant current value. It should be noted that this control cannot guarantee that the robot will not slip and fall, but it can avoid excessive joint loading. The efficacy of this control for tension adaptation was validated through experiment.

This paper proposes a novel motion design for a snake robot to move freely in a space between two adjacent walls. Snake robots are expected to be useful in several difficult environments because of their high degrees of freedom. Particularly, they are suitable for use in narrow spaces. However, freely moving in narrow spaces, such as spaces between two adjacent walls, remains an open problem. In this study, inspired by helical rolling motion, which is used to move on a pipe, we propose a novel motion method that enables a snake robot to move freely in a narrow space between two adjacent walls. The motion and model are validated using physical simulations.

This paper proposes a method for designing the 3D deformable shape of a continuum robot based on genetic algorithm optimization for the arrangement of tendon guides. We introduce plain and penetration models that are classified based on tendon configurations. A combination of these models produces 3D deformations. Optimizing the arrangement of the tendon guides extends the behavior of the prototype by providing a distribution in its curvature. We designed a model to simulate the deformed shape of the prototype and used a genetic algorithm to determine the optimal solution for the parameters to be mathematically suited to the given shapes. Additionally, we built prototypes using the applied parameters and demonstrated them experimentally. We also verified the continuum robots with optimized parameters by comparing them with pre-optimized parameters. The results of this study can contribute to improving the dexterity and versatility of the movements of continuum and biomimetic robots using only a few actuators.

This study describes a method for applying an extended Kalman filter to a snake robot, which moves through a pipe using a helicoidal rolling motion. The filter estimates the helix radius, amount of twisting, and helix pitch to adapt to changes in the diameter inside the pipe. Additionally, offset values are added to these estimated values to propel the snake robot along the pipe autonomously. In particular, we experimentally demonstrated the effect of helix pitch on friction force and proposed a parameter-setting strategy that accounts for the range of motion of the joints. Finally, we validated the results of the proposed method through experiments on an actual robot.

The maintenance and inspection of pipelines are crucial in various industries, including oil and gas, water supply, and sewage systems. Traditional methods often involve significant human labor, risks, and costs. Inspired by biological systems, soft robotics offers innovative solutions with the potential to navigate complex and confined environments. This study discusses the development of soft pipe inspection robots equipped with vibration cilia for enhanced mobility and inspection capabilities. The cilia are driven by a vibration motor that can generate controlled vibrations for propulsion. The coordinated movement of the cilia allows the robot to navigate vertically or through complex pipe networks. A notable advancement in this study is the robot’s capability to move under water, which thereby enables its locomotion across stagnant water in pipes. This study also discusses the basic design, modeling, performance analysis, and waterproof compactability verified through experiments. Its flexible design and bio-inspired locomotion offer a safer, more efficient, and cost-effective solution for maintaining vital pipeline infrastructure.

This paper proposes a hanging motion for snake robots by utilizing half-hitch knot tying, which is a type of rope work. The proposed method prevents a robot from falling off a pipe by tying it to the pipe. In addition, the robot can hang from a pipe by grasping it using the knotting part. The parts other than the knotting part can be operated arbitrarily and applied to various actions. We propose a transporting motion as one of the applications of the hanging motion. The effectiveness of the proposed motion was experimentally verified using an actual robot.

The purpose of this study is to develop a snake-like robot for cable laying. Cable laying is one of the tasks that inevitably occur in construction work. Cable laying is generally performed manually by workers in high and narrow spaces, such as cable racks installed in ceilings and ceiling spaces. Therefore, it involves significant risks, such as falls. To ensure worker safety and enable anyone to perform the task, automation and labor-saving through robots are anticipated. Therefore, this study aims to develop a snake-like robot that pulls a lead cable through traveling wave inspired by workers’ cable-laying actions. We verify whether this traveling wave can achieve propulsion in different environments, such as flat surfaces, cable racks, and ceiling spaces, through simulations and real-world experiments. The simulation and experiment results confirm that the traveling wave is effective for propulsion in cable racks and ceiling spaces. Based on these results, it was required to keep the head horizontal to the ground even during traveling wave to allow environmental inspection using a camera mounted on the snake-like robot’s head. Therefore, we established a method to achieve propulsion with traveling wave while maintaining the head’s horizontal position using Fourier series expansion. By implementing this, we achieved propulsion with reduced head oscillation.

Multi-purpose module system (MMS), which is one of the module robots, consists of locomotion, sensor, communication, and function modules. The MMS can be transformed into a series-connected form or a quadruped form, following which appropriate sensors can be added. Therefore, the MMS can be used as a rescue robot in an unknown situation. This study presents an overview of each of the modules that comprise the developed MMS, as well as an overview of each of the forms in which they are combined. Considering that the MMS feature can freely combine different types of modules, we developed MMS-D01, which combined serpentine and wheeled propulsion, and MMS-V02, which combined Mecanum-wheeled propulsion and stable traveling using joint control. These developed MMSs were evaluated under various conditions.

This paper presents a novel locomotion soft robot that exploits the properties of auxetic structures to achieve bio-inspired undulatory locomotion. To reduce the dependence on computation and control strategies, we propose to develop a soft structure using a combination of positive Poisson’s ratio lattice structure and negative Poisson’s ratio lattice structure that creates a dorsoventral undulating wave pattern under compressive load. This is combined with a laterally undulating gait pattern exhibited by giant salamanders. The soft structure is actuated with nylon cables attached to servo motors, mimicking muscles. We use finite element analysis (FEA) methods to accurately model the soft structure’s deflection pattern, which is then used to create a control strategy for the robot. We develop a mathematical model and a subsequent gait pattern based on the sequential actuation of the nylon cables. The gait was experimentally tested and further improved with closed-loop error compensation. The research proves linear locomotion is possible through the proposed design with the lowest computational requirements.

This study proposes a novel approach for a snake robot traversing an environment composed of two planes, one fixed and the other varying in inclination. Instead of adapting to the environment, the robot propels itself by deliberately changing the environment into a form that facilitates mobility. Assuming that the robot straddles two planes, the inclination of the planes is changed by controlling the motion of the part that straddles them. The proposed method changes the inclination only through movement of the robot, which straddles the planes. Therefore, other body parts can be used in conjunction with other motions using conventional methods. The effectiveness of the proposed method and its limitations were verified through physical simulations. The simulation results confirmed that the snake robot can modify the inclination of the plane if its posture is suitable for modifying the environment.

Ostrich neck-inspired manipulators have attracted attention in the field of bio-inspired robotics. They achieve unique movements that are difficult for conventional robots, owing to their flexibility. However, it is difficult to mimic the length, mass, and actuation redundancy of ostrich necks. This is because the longer and heavier the robotic arm, the greater is the load on the joints. Furthermore, if a robotic arm exhibits actuation redundancy, its structure and control become more complex. In this study, we developed a hybrid RobOstrich manipulator with both intrinsic and extrinsic actuations. This is the third-generation of the RobOstrich series. The manipulator consists of a servomotor attached to each joint that performs intrinsic actuation and two servomotors on the base that perform extrinsic actuation through wires. We conducted an experiment to reproduce the rolling pattern, which is a unique movement of the ostrich neck, to verify the effect of hybrid actuation. The results indicated that the joint angle error and required torque were reduced by applying hybrid actuation.

This paper presents an underwater snake robot composed of submersible actuators designed for minimal friction, a lubricant-free gear reducer, and no waterproof sealing. This makes it suitable for direct exposure to water. In particular, this paper focuses on underwater interactive tasks with an object. Static force analysis for straightforward tasks, such as the wrapping of a pole structure, is conducted. Experiments were performed to evaluate the snake robot outside a water environment. The results indicated that the static model was valid, although the errors were not negligible. The potential of executing various tasks with this sensorless underwater snake robot, such as wrapping around the pole and its collection or turning on/off a lever underwater, is presented.

Flatworms exhibit remarkable pedal-wave-driven locomotion abilities through their dorsoventrally flattened, bilaterally symmetrical bodies, which glide smoothly across various surfaces. This study introduces a bio-inspired mobile robot prototype designed to mimic flatworm movement that leverage the advantages of pedal locomotion on challenging terrains. The robot design includes a mesh-like structure with interconnected body modules linked via multi-degree-of-freedom joints for enhanced movement versatility. A modified universal joint that functions as a constant-velocity joint connects the modules, thereby enabling complex motion patterns. We explored four types of traveling waves, inspired by gastropod locomotion to achieve diverse movements, including translational, spinning, and omnidirectional motions. This study comprehensively examines the movement characteristics and performance of the prototype, highlighting its potential applications in complex environments in which traditional locomotion methods are less effective.

The automatic generation of dynamic facial expressions to transmit the internal states of a robot, such as mood, is crucial for communication robots. In contrast, conventional methods rely on patchwork-like replaying of recorded motions, which makes it difficult to achieve adaptive smooth transitions of the facial expressions of internal states that easily fluctuate according to the internal and external circumstances of the robots. To achieve adaptive facial expressions in robots, designing and providing deep structures that dynamically generate facial movements based on the affective state of the robot is more effective than directly designing superficial facial movements. To address this issue, this paper proposes a method for automatically synthesizing complex but organized command sequences. The proposed system generated temporal control signals for each facial actuator as a linear combination of intermittently reactivating decaying waves. The forms of these waves were automatically tuned to express the internal state, such as the arousal level. We introduce a mathematical formulation of the system using arousal expression in a child-type android as an example, and demonstrate that the system can transmit different arousal levels without deteriorating human-like impressions. The experimental results support our hypothesis that appropriately tuned waveform facial movements can transmit different arousal state levels, and that such movements can be automatically generated as superimposed decaying waves.

Detecting humans in images not only provides vital data for a wide array of applications in intelligent systems but also allows for the classification of specific groups of individuals for authorization through various methods based on several examples. This paper presents a novel approach to classify persons wearing a face mask as an example. The system utilizes an omnidirectional camera on the mobile robot. This choice is driven by the camera’s ability to capture a complete 360° scene in a single shot, enabling the system to gather a wide range of information within its operational environment. Our system classifies persons using a deep learning model by gathering information from the equirectangular panoramic images, estimating a person’s position, and computing robot path planning without using any distance sensors. In the proposed method, the robot can classify two groups of persons: those facing the camera but without face masks and those not facing the camera. In both cases, the robot approaches the persons, inspects their face masks, and issues warnings on its screen. The evaluation experiments are designed to validate our system performance in a static indoor setting. The results indicate that our suggested method can successfully classify persons in both cases while approaching them.

This study explores advanced methods for underwater visual surveys in the photic zone using low-cost autonomous underwater and surface vehicles to enhance marine ecosystem monitoring and analysis. It addresses the challenges of underwater photogrammetry, including data post-processing and analysis, by introducing geo-reference estimation techniques for autonomous-under-vehicle-mounted cameras. Through a novel validation method based on trajectory overlaps and application to real-world datasets, the research demonstrates the effectiveness of these approaches in complex underwater environments. The findings contribute to improving the accuracy of three-dimensional reconstructions of the seafloor, offering significant implications for marine conservation and ecosystem management.

Recently, the population of agricultural workers in Japan has been declining and aging. As a result, labor shortages have become a serious problem in the agricultural industry. However, the strong dependence on food imports has become a problem. To address this situation, it is necessary to increase the efficiency of food production by automating agricultural work. In this study, we focus on transportation in farming, and develop an unmanned transportation truck. Farm roads are often unpaved or otherwise uneven, and the surrounding environment changes dramatically depending on road surface conditions, vegetation, weather, and season. To realize an unmanned transportation system, achieving robust environmental recognition and operational control is important. Although it is almost certain that no single method can manage all situations for this goal, as part of the system, we propose a method for generating a target path for farming environments using 3D LiDAR (Light Detection and Ranging), and apply a control law to follow the path on uneven surfaces robustly. Furthermore, we generate two types of paths, one based on the center of the drivable area and the other based on road surface geometry, and integrate them into a target path based on their reliability. A nonlinear path-following control law is designed to follow the target path. The proposed method was applied to an experimental truck, and stability was achieved on a real farm road.

This study proposes a micro-logistics node as a new infrastructure envisioned for future convenience stores. This system automates the management of products on shelves, reduces the workload on store clerks, and provides an entirely new shopping experience with optimal displays based on the time and customers visiting the store. Automated warehouse technology has recently advanced, and the storage and removal of items from warehouse racks have been successfully automated. However, when considering implementation in convenience stores, robotic systems must adapt to their unique conditions: operation in limited backyard space, handling a wide variety of products with different sizes and shapes, and minimization of dead space in product displays. To address these challenges, this study developed a robot system that travels on vertical and horizontal tracks installed behind display shelves, and places products stored in special trays at any coordinate on the shelves.

This paper describes three-dimensional (3D) reconstruction processes introducing an image selection method to efficiently generate a 3D model from an image sequence. To obtain suitable images for efficient 3D reconstruction, we applied the image selection method to remove redundant images in an image sequence. The proposed method can select suitable images from an image sequence based on optical flow measures and a fixed threshold. As a result, it can reduce the computational cost for 3D reconstruction processes based on the image sequence acquired by a camera. We confirmed that the computational cost of 3D reconstruction processes can be reduced while maintaining the 3D reconstruction accuracy at a constant level.

Forceps-type mini-positron emission tomography (mini-PET) has been proposed as an intraoperative device for examining metastatic lymph nodes in the treatment of esophageal cancer. Although this forceps-type mini-PET detects cancer by radiation measurement, the scissor-like tip of the device affects the measurement accuracy. Therefore, to improve the detection sensitivity of the forceps-type mini-PET without depending on the operator, we fabricated a forceps tip mechanism using a parallel-link for parallel opening and closing motions, and verified the parallel motion and the force required for opening and closing. Consequently, we confirmed parallel motion from the opening and closing widths of the tip detectors. In addition, we confirmed that the forces required for opening and closing were significantly smaller than those required for the conventional mechanism.

The maintenance of public toilets, such as those found in convenience stores, presents challenges in the era of limited human resources. Consequently, the development of an automatic toilet cleaning system is necessary. The detection of trash on the toilet floor is an essential component of the automatic toilet cleaning system. However, this process presents its own set of challenges, including the unpredictability of the types and locations of the trash that may be present. This study proposes a system for detecting solid waste on the toilet floor by applying the structure and feature similarity index method of image. The difference in the structure and features of the reference and actual images can indicate the trash that appears on the toilet floor. This study also proposes a method for determining the threshold value of similarity feature measurement. The experimental results demonstrate that the proposed detection system is able to produce a detection success rate of up to 96.5%. Additionally, the system proves capable of detecting small objects, such as human hair, under specific conditions. This method offers a resource-efficient solution to the challenges faced in maintaining public toilet cleanliness.

Humans maintain postural stability while walking by modulating their spatiotemporal walking features. It is crucial for humans to be able to restore stability in the event of a transient loss. However, the ease of adjusting postural stability has not yet been investigated extensively. This study applied manipulability, a concept widely used in robotics, to analyze the margin of stability (MoS), a measure of dynamic postural stability. The MoS values along each of the anterior and mediolateral directions were modeled as a function of spatiotemporal gait parameters, and the manipulability of the MoS was computed. We observed differences in manipulability between two age groups (60 healthy elderly adults and 60 healthy young individuals in their 20s) from an open database. The manipulability of the elderly was significantly higher than that of the young, suggesting that the elderly employed walking postures that allowed them to adjust their stability with relative ease. Furthermore, for the young group, the manipulability tended to be low when the mediolateral stability was low, with a correlation coefficient of 0.67. In contrast, the elderly group did not exhibit this relationship, showing differences in walking strategies between young and elderly individuals. The manipulability analysis of dynamic gait stability provides insights into revealing human gait strategies.

In Japan, the percentage of traffic fatalities involving individuals aged 65 years and older is higher than that of other age groups. This issue can be addressed by having elderly individuals reflect upon their driving habits. Currently, this involves repeatedly attending training sessions at driving schools, which can be challenging due to time and location constraints. Hence, we develop a driving-review robot that allows elderly people to self-assess their driving skills in their homes. In developing this robot, we identified two crucial factors: “support continuity,” which relates to the extent to which individuals use the robot over an extended period, and “support acceptability,” which measures the willingness of users to accept advice from the robot. Both factors are assumed to be influenced by the attachment and connection felt by individuals toward the robot. Previous studies suggest that attachment can be enhanced via voluntary naming of the robot. Therefore, this study investigates the relationship between naming a drive-reviewing robot and its effect on support continuity and acceptance, as well as its effect on improving driving behavior via multiple instances of self-assessment. The results suggest that the presence and type of honorifics used during the naming process can affect individuals’ impressions of the robot. Furthermore, naming the robot with Japanese honorifics such as “-kun” or “-chan” and engaging in repeated driving self-assessment sessions may enhance support continuity and potentially increase the time spent on verifying the surroundings during driving, thus improving driving behavior.