Snake-like Robot Research Articles

Design of the Crawler Units: Toward the Development of a Novel Hybrid Platform for Infrastructure Inspection

Inspections of industrial and civil infrastructures are necessary to prevent damages and loss of human life. Although robotic inspection is gaining momentum, most of the operations are still performed by human workers. The main limiting factors of inspection robots are the lack of versatility as well as the low reliability of these devices, since they need to operate in a non-structured environment. In this work, a novel Hybrid Platform for inspection in industrial contexts is proposed, focusing on the design and testing of the Crawler Unit. The goal is to solve versatility related issues exploiting modularity and self-reconfigurability. The Hybrid Platform consists of three main systems: a mobile Main Base and two Crawler Units. Each would operate independently, accomplishing specific tasks. Docking interfaces, on each device, allow the systems to reconfigure into different robots. The Crawler Unit operates in constrained environments and narrow spaces. The Main Base patrols wide areas and deploys the Crawler Units near the inspection site. For dealing with challenging conditions, the two Crawler Units can dock together, reconfiguring into a snake-like robot. Additionally, once docked to the Main Base, the two Crawlers can operate also as robotic arms, providing manipulation abilities to the platform. The first version of the Crawler Unit exhibited an interesting performance over flat and uneven terrains. To extend the mobility of this robot, a second version was developed, introducing some innovations in the system design. These innovations provided the Crawler Unit with advanced mobility in the vertical plane, thus allowing the robot to deal with more complex scenarios such as crossing gaps, overcoming obstacles and lifting the modules.

Frictional Properties of a Novel Artificial Snakeskin for Soft Robotics

Although snake-like robots are only rarely used in real applications, numerous designs have been proposed by different researchers. In addition to the capability of grasping objects by bending their body around them, snakes travel in various environments by using different gaits. To move forward, they need a skin which provides friction anisotropy to the ground. The designs of snake-like robots vary in their actuation mechanism as well as in the design of their artificial skin. In this work, we present a novel design of an artificial snakeskin. The design is related to an application in soft robotics, but is not restricted to this type of robot. Since soft robots are flexible and can stretch, our artificial skin is also able to. It is inspired by the belly of snakes and provides friction anisotropy in forward-reverse direction. To achieve this, we embed scales with a specific angle of attack into a flexible base body. In the experimental investigation of the artificial snakeskin, we determine the friction anisotropy for two base body materials with different stiffness and for three angles of attack. Although the development of the artificial skin is at an early stage, the results of the experimental investigation are promising. The dynamic behavior of the artificial snakeskin indicates that a flexible base material reduces friction in forward direction and increases friction in reverse direction, thus enhancing friction anisotropy. Furthermore, the results obtained give important information for further design improvements in future.Presentation of a modular and stretchable artificial snakeskin Systematic investigation of the frictional properties when changing the angle of attack of the scales and the softness of the base material the scales are embedded in A soft base material increases friction anisotropy and reduces inaccuracies of hand manufacturing Demonstration of a soft robotic actuator which uses the artificial snakeskin for crawling.

The Impact of Dorsal Fin Design on the Swimming Performance of a Snake-Like Robot

Lampreys&#x2019; posterior dual dorsal fins can function as a thrust booster. In addition, the fin-fin interaction of these dorsal fins enables utilization of the energy from the wake, making this species one of the most efficient swimmers. Thus, this dorsal fin configuration can serve as a great source of inspiration for improving the swimming speed and efficiency of bioinspired underwater robots. We perform a systematic experimental and computational study to understand the impact of a dual dorsal fin design on swimming speed and efficiency of an underwater snake-like robot. In the proposed dorsal fin structure, the hind fin often operates in the wake of the fore fin. Hence, its performance is affected by the vortices shed by the fore fin. The spacing of the two dorsal fins and the robot&#x2019;s oscillation parameters significantly impact the swimming performance of the snake-like robot. Four different spacings ranging from 0 to 3 link gaps were tested at three different amplitudes (<inline-formula><tex-math notation="LaTeX">$15^\circ$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$30^{\circ }$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$45^{\circ }$</tex-math></inline-formula>) and angular velocities (2, 3 and 4 rad/s). It was found that changes in the spacing and kinematic parameters would significantly affect the interactions of the vortices shed from the fore and hind fins. This interaction, in turn, affects the vortex formation on the hind fin, resulting in changes in wake strength and formation direction, which would significantly affect the swimming speed and efficiency of the underwater snake-like robot. These findings provide better understanding of how dual dorsal fins and the respective fin-fin interactions affect the swimming performance and can be used as guidelines for designing bioinspired underwater robots.

ARCSnake: Reconfigurable Snakelike Robot With Archimedean Screw Propulsion for Multidomain Mobility

Exploring and navigating in extreme environments, such as caves, oceans, and planetary bodies, are often too hazardous for humans, and as such, robots are possible surrogates. These robots are met with significant locomotion challenges that require traversing a wide range of surface roughnesses and topologies. Previous locomotion strategies, involving wheels or ambulatory motion, such as snake platforms, have success on specific surfaces but fail in others which could be detrimental in exploration and navigation missions. In this paper, we present a novel approach that combines snake-like robots with an Archimedean screw locomotion mechanism to provide multiple, effective mobility strategies in a large range of environments, including those that are difficult to traverse for wheeled and ambulatory robots. This work develops a robotic system called ARCSnake to demonstrate this locomotion principle and tested it in a variety of different terrains and environments in order to prove its controllable, multi-domain, navigation capabilities. These tests show a wide breadth of scenarios that ARCSnake can handle, hence demonstrating its ability to traverse through extreme terrains.

Snake Robot Gripper Module for Search and Rescue in Narrow Spaces

This letter presents a gripper module for a snake-like robot to perform search and rescue tasks in a narrow space. The proposed gripper module has three features: (1) It can accommodate the fingers inside its body. (2) It has three fingers that can grip objects with irregular surfaces stably. (3) One of the fingers is equipped with a camera on the fingertip to search in a narrow space. To implement the above features in a small, light, and compact gripper module, we propose a novel design of a gripper module with three fingers and eight degrees of freedom. The joint configuration of the proposed gripper is unique compared with a general-type gripper. A prototype of the proposed gripper module has been integrated into a snake-like robot to demonstrate its capability of performing rescue tasks in a collapsed environment. The three features of the proposed gripper module are experimentally verified: it is light (0.4 kg), small (less than 68 mm in diameter), and powerful (grasping force = 2.48kgf).

Obstacle avoidance path scheme of snake robot based on bidirectional fast expanding random tree algorithm

With the continuous innovation and development of related technologies in the field of robotics, various robots have emerged in large numbers, the application scenarios of robots are becoming more and more complex, and the requirements for robot technology are also getting higher and higher. As an indispensable part of robotics research, path planning technology has very important research and application value. As a new movable snake-shaped robot, the snake-shaped robot has always been a research hotspot in the field of snake-shaped robots due to its multi-gait movement ability and strong environmental adaptability. Among the various motion forms of the snake-shaped robot, the winding motion has the highest efficiency, and the snake-shaped robot in this motion form can also assist itself in its movement by contact with obstacles. However, there are few researches on the obstacle-assisted motion of snake-like robots, and the algorithm for solving collision dynamics is relatively simple. Therefore, it is necessary to conduct in-depth research on obstacle-assisted motion snake-like robots. The trajectory planning algorithm of the multi-NAO snake robot is studied. First, it analyzes the basic principles and implementation steps of the RRT algorithm and evaluates its advantages and disadvantages. On this basis, an improved fast-expanding random algorithm is proposed for the shortcomings of the RRT algorithm. Combining the advantages of the global search of the RRT algorithm, it is necessary to introduce an appropriate local search algorithm. Under the premise of ensuring that the path can be generated, a certain algorithm is added to improve the smoothness of the path, in order to reduce the turning time of the snake-like robot when it walks, and improve the search efficiency. Aiming at the randomness of RRT when generating random tree nodes, other algorithms are purposefully introduced to enable it to grow toward the target point. Path planning simulations verify that the improved two-way rapid expansion random tree algorithm has significantly improved search speed and search efficiency compared with Basic-RRT and Bi-RRT algorithms, with shorter average planning time and higher success rate, the generated path is smoother. Improved algorithm can not only avoid static global obstacles in a dynamic environment, but also efficiently avoid sudden dynamic obstacles. The real-time dynamic obstacle avoidance experiments based on the FANUC snake-shaped robot guiding the anthropomorphic obstacles to move and rotate in translation and the snake-shaped robot dynamically avoiding real human arms verify that the proposed algorithm can dynamically avoid regular and irregular moving obstacles online in time. When the number of obstacles is 3, the number of successful plans is 49, and the planning time is 55 ms; when the number of obstacles is 12, the number of successful plans is 40, and the planning time is 88.9 ms. Obviously, the increase in the number of obstacles leads to a decrease in the number of successful planning and an increase in planning time.

Design and Experiments of a Compact Self-Assembling Mobile Modular Robot with Joint Actuation and Onboard Visual-Based Perception

Modular robots have the advantage of self-assembling into a large and complex structure to travel through territories beyond an individual robot’s capacity. A swarm of mobile robots is combined through mechanical interconnection and joint actuation to achieve a linked or articular configuration. In this paper, to enhance the perception, actuation and docking capacity of modular robots, a parallel mechanism-based docking system and onboard visual perception system are proposed in the design of a novel compact self-assembling mobile modular robot (SMMRob). Each module is self-contained, with a sensing or joint function. The robot modules can dock with each other based on relative positioning, which employs the visual perception of passive markers or active infrared signals in different localizations. Performance experiments were conducted to evaluate the robot module. Docking experiments were performed, along with an analysis of the success and failure results. The self-assembly of snake-like and quadruped robots was achieved in response to different environments, including an obstacle, gap or stair, and experiments were performed on self-assembly into a snake-like structure.

Impact of caudal fin geometry on the swimming performance of a snake-like robot

Eels and sea snakes are known for long migrations and high endurance cruising and can be great sources of inspiration for underwater robots. This study employs both computational and experimental techniques to explore the impact of caudal fin design on the swimming performance of a snake-like robot. The caudal fin geometry is systematically varied by changing the leading edge and trailing edge angles. Inspired by sea snakes, the robot mimics an anguilliform swimming gait. Robotic experiments and computational fluid dynamics (CFD) simulations are carried out with different caudal fin geometries. The results show that the snake-like robot achieves the best swimming speed and efficiency at an 85°leading edge angle and a 120°convex trailing edge angle. In addition, the numerical simulation results show that the wake structure formed by the snake-like robot consists of two parallel disconnected verse van Karman vortex rings. When the leading edge angle is slightly below 90°the body vortex merges and interacts with the caudal fin’s vortex. This interaction contributes strongly to wake construction and significantly enhances swimming speed and efficiency.

Energy-Efficient Gait Optimization of Snake-Like Modular Robots by Using Multiobjective Reinforcement Learning and a Fuzzy Inference System

Snake-like modular robots (MRs) are highly flexible, but, to traverse a challenging terrain or explore a region of interest, MR needs to attain efficient locomotion depending on a tradeoff between objectives like forward velocity and power consumption of the robot. The objectives can vary with different weights depending upon the situation, reflecting relative objective importance. This study developed a multiobjective reinforcement learning algorithm based on a fuzzy inference system (FI-MORL) to select the most appropriate gait parameters of snake-like MRs according to the objective weights. The developed algorithm employs a fuzzy inference system to reduce the number of states in an environment, which results in faster learning. The proposed approach uses the previously learned experience to rapidly achieve the best objective values in response to a change in weights. While setting equal importance to the objectives, FI-MORL delivers superior performance than single-objective reinforcement learning algorithms by consuming 2% less power and gaining 2.5% higher velocity since it mitigates the effect of weight change, similar performance found comparing Actor-Critic algorithm. Likewise, the proposed method outperforms by consuming 14% less power and achieving 11% higher velocity than traditional methods like Proximal Policy Optimization, Deep Q-Network, and Vanilla Policy Gradient. Even after weight change, FI-MORL achieved a 14% higher reward than the above methods. The proposed FI-MORL framework can effectively converge quicker and efficiently handle the changes in objective weights.

Lateral Undulation, and a Snake-like Robot with Multiple Steering Systems

Lateral Undulation, and a Snake-like Robot with Multiple Steering Systems

Study on Snake-like Robot with Suspension

Study on Snake-like Robot with Suspension

Curriculum-based reinforcement learning for path tracking in an underactuated nonholonomic system

Underactuated mechanical systems with nonholonomic constraints find applications in bioinspired robotics, such as snake-like robots and more recently in fish-like aquatic robots. Animal locomotion suggests that in such bioinspired robots, gaits or cyclic changes in kinematics or shape variables lead to efficient and agile motion. Path tracking in such nonholonomic systems that are not purely kinematic can be a challenging problem. In this paper we consider the problem of path tracking by a modified Chaplygin sleigh with a ‘tail’ which is a four degree of freedom nonholonomic system, possessing a single internal reaction wheel as an actuator. We develop a curriculum based deep Reinforcement Learning (RL) optimal control approach for simultaneous velocity and path tracking for this system. The curriculum based learning approach first leads to a policy for optimal tracking of limit cycles in a reduced velocity space and then in a next step to track a path. This curriculum approach allows an RL agent to learn the ’mechanics on invariant manifolds’ of the system and can be a useful approach in the motion control of high degree of freedom robots with increasing model complexity.

A Survey on Snake Robot Locomotion

Snake robots have been a topic of discussion among researchers for decades. They are potentially strong enough to bring substantial contributions to the fields which are unsafe/ narrow/ dirty/ hard reachable to human operators, such as inspections, rescue missions, firefighting, etc. Though the inventions of the wheel and legged mechanisms are amazing, they often fail when coming to these scenarios. Terrain adaptability is the vital essence of locomotion over constrained surfaces in biological snakes. But how this natural adaptability is accomplished in snake-like robots? Therefore, this paper focuses a study on factors behind the recreation of a physical snake, like the kinematics and dynamics modelling, mechanical design, and locomotion control approaches from existing literature. With their feature comparison, the simulators available for verifying the mathematical model and the feasibility of the mechanical design are also made for researchers new to the field.

The History, State of Art, and Future Prospects for Snake-like and Soft Robots Study

The History, State of Art, and Future Prospects for Snake-like and Soft Robots Study

Obstacle Avoidance and Environmental Adaptability Analysis of Snake-like Robot Based on Deep Learning

Aiming at the problems of high complexity and low accuracy of visual depth map feature recognition, a graph recognition algorithm based on principal component direction depth gradient histogram (pca-hodg) is designed in this study. In order to obtain high-quality depth map, it is necessary to calculate the parallax of the visual image. At the same time, in order to obtain the quantized regional shape histogram, it is necessary to carry out edge detection and gradient calculation on the depth map, then reduce the dimension of the depth map combined with the principal component, and use the sliding window detection method to reduce the dimension again to realize the feature extraction of the depth map. The results show that compared with other algorithms, the pca-hodg algorithm designed in this study improves the average classification accuracy and significantly reduces the average running time. This shows that the algorithm can reduce the running time by reducing the dimension, extract the depth map features more accurately, and has good robustness.

Development of snake-like robot with wire drive mechanism

Development of snake-like robot with wire drive mechanism

Position estimation of paddy field weeding snake-like robot by GNSS

Position estimation of paddy field weeding snake-like robot by GNSS

Locomotion Control of Snake-like Robot utilizing Friction Forces: Stability Verification of Model Following Servo Controller

Locomotion Control of Snake-like Robot utilizing Friction Forces: Stability Verification of Model Following Servo Controller

Designing Novel Decentralized Control Scheme of Snake-like Robot by Understanding Essential Mechanism of Snake Locomotion

Designing Novel Decentralized Control Scheme of Snake-like Robot by Understanding Essential Mechanism of Snake Locomotion

A Muscle-Driven Mechanism for Locomotion of Snake-Robots

This paper presents the concept of muscle-driven locomotion for planar snake robots, which combines the advantages of both rigid and soft robotic approaches to enhance the performance of snake robot locomotion. For this purpose, two adjacent links are connected by a pair of pneumatic artificial muscles wherein an alternate actuation of these soft actuators causes a rotational motion at the connecting joints. The muscle-based actuated linkage mechanism, as a closed six-linkage mechanism, was designed and prototyped. The linear motion and force generation of the pneumatic artificial muscle was experimentally characterized using isotonic and isometric contraction experiments. A predictive model was developed based on the experimental data to describe the relationship between the force–length–pressure of the PAMs. Additionally, the muscle-driven mechanism was kinematically and dynamically characterized based on both theoretical and experimental studies. The experimental data generally agreed with our model’s results and the generated joint angle and torque were comparable to the current snake-like robots. A skx-link planar snake robot with five joints, five pairs of antagonistic muscles, and an associated pneumatic controller was prototyped and examined for simple movements on a straight-line. We demonstrated the muscle-driven locomotion of the six-link snake robot, and the results show the feasibility of using the proposed mechanism for future explorations of snake robot locomotion.