Crawler Robot Research Articles

Step recognition using LiDAR and navigation considering step entry direction for skid-steer robots

In recent years, studies on autonomous mobile robots for outdoor use have been actively conducted. In these studies, skid-steer robots such as crawler robots are often used. These mechanisms are not good at diagonally entering steps such as curbs, so it is necessary to consider the step entry direction for navigation of these robots. However, there are few previous studies that deal with detection of low height steps on the ground, path planning that considers the step entry direction, and tracking control, in a unified manner. In this study, we present a ground surface classification using LiDAR scan characteristics, a path optimization using quadratic programming with the step entry direction constraint, and a tracking control using TOPP to accurately follow the path. As a result of the experiment, we confirmed that it was able to detect 0.1 m height steps and climb over them by entering perpendicularly to the steps.

Mobile crawler robot for seed sowing and route planning through neuro-diffuse control

The main objective of this project is to build a mobile terrestrial robot that allows the sowing of seeds of various types of plants that are cultivated in an artisanal way. A structure based on tracked locomotion has been designed that involves the use of several sensors, DC motors, and control systems based on two Arduino boards, which together allow the mobile robot to interact with the irregular environment through which it moves. The locomotion process carried out by the seeding robot is configured through an HMI interface implemented on a touch screen, where the user chooses the type and quantity of seeds to be sown so that the robot then follows an autonomous rectilinear trajectory which is supervised and corrected utilizing a neuro-diffuse control such as ANFIS. In addition, the mobile robot has a battery feeding and charging system through solar panels, which gives it complete autonomy to carry out the work entrusted to it.

Research on the overturning phenomenon of firefighting and rescue crawler robots when climbing up and down stairs

Research on the overturning phenomenon of firefighting and rescue crawler robots when climbing up and down stairs

A Motion Planner Based on Mask-D3QN of Quadruped Robot Motion for Steam Generator.

Crawling robots are the focus of intelligent inspection research, and the main feature of this type of robot is the flexibility of in-plane attitude adjustment. The crawling robot HIT_Spibot is a new type of steam generator heat transfer tube inspection robot with a unique mobility capability different from traditional quadrupedal robots. This paper introduces a hierarchical motion planning approach for HIT_Spibot, aiming to achieve efficient and agile maneuverability. The proposed method integrates three distinct planners to handle complex motion tasks: a nonlinear optimization-based base motion planner, a TOPSIS-based base orientation planner, and a Mask-D3QN (MD3QN) algorithm-based gait motion planner. Initially, the robot's base and foot workspace were delineated through envelope analysis, followed by trajectory computation using Larangian methods. Subsequently, the TOPSIS algorithm was employed to establish an evaluation framework conducive to foundational turning planning. Finally, the MD3QN algorithm trained foot-points to facilitate robot movement along predefined paths. Experimental results demonstrated the method's adaptability across diverse tube structures, showcasing robust performance even in environments with random obstacles. Compared to the D3QN algorithm, MD3QN achieved a 100% success rate, enhanced average overall scores by 6.27%, reduced average stride lengths by 39.04%, and attained a stability rate of 58.02%. These results not only validate the effectiveness and practicality of the method but also showcase the significant potential of HIT_Spibot in the field of industrial inspection.

Kresling Origami With Differentiation Flaw Design for Multidirectional Crawling Robot

Kresling Origami With Differentiation Flaw Design for Multidirectional Crawling Robot

Ground Adaptability of Crawler Mobile Robots with Sub-Crawler Rotary Joint Compliance

Remote-controlled mobile robots are expected to be used in difficult- or impossible-to-access environments for inspection workers and responders, such as in investigations and search activities at accident/disaster sites and inspection/investigation work at plants/infrastructure. Among ground mobile robots, crawler mobile robots with sub-crawlers (also known as ground-adaptive crawler robots) excel at in-ground adaptability and stack escape; however, their operators require advanced remote-control technology and experience. Therefore, the introduction of semi-autonomous control to assist the operator is required. In this study, the principle of the pushing-up sequence and the possibility of mobiligence emerging from interaction with obstacles caused by the robot movement were described. In addition, the sub-crawler rotary joint’s compliance, which significantly contributes to ground adaptability, was hypothesized, and a compliance control system design method that uses the sub-crawler constraint angle as a design condition was proposed. It was confirmed that the model robot for the evaluation, which used the proposed method, could adapt to unknown obstacles without measuring their height and shape and traverse them based on experimental results. In addition, based on the numerical calculation results, it was determined that the optimum solution for the restriction angle of the sub-crawler was approximately 35°–50° from the perspective of propulsive force and tumble stability.

An Origami-Enabled Soft Linear Actuator and Its Application on a Crawling Robot

Abstract Soft linear actuators have strong deformation ability and good environmental adaptability, which have been widely used in soft robot design. However, little work has focused on designing soft linear actuators with balanced performances, featuring fast driving speed, large output displacement, being lightweight, and miniaturization. Herein, we present a novel soft linear actuator design based on the Kresling origami structure. By driving the Kresling tubes with a servo motor, the soft linear actuator has good compliance and strong environmental adaptability and can achieve a driving speed, large driving force, and high control precision comparable to the traditional electrical motor. The analytical models of the Kresling tubes and the whole actuator are respectively derived to analyze the mechanical properties, determine the optimal geometry of the Kresling tube, and evaluate the driving performance of the whole actuator. The actuator prototype is fabricated by 3D printing, and the actual driving performance is tested. It is shown that the prototype can achieve a maximum output displacement of 18.9 mm without payload or 16 mm under a payload of 30 N. Finally, as a case study, the soft linear actuator is applied to a crawling robot, where the maximum moving speed of 28 mm/s is reached.

Pipe Crawler Robot

This pipe inspection robot aims at detecting the exact location of leakage and clearing the blockages, thus removing human factors from labor-intensive and dangerous work, thereby reducing the number of accidents that happen due to the lack of regular inspection. Detection Pipe leakage, water distribution system. An autonomous pipe crawler robot is designed to navigate through pipelines, offering a practical and efficient solution for inspecting and monitoring the condition of pipe interiors. This robot leverages advanced locomotion mechanisms and control strategies to maneuver through various pipe diameters and configurations, including straight sections, bends, and junctions. Equipped with sensors and cameras, it can detect anomalies such as cracks, corrosion, blockages, and leaks, providing real-time, high-resolution imagery and data. This technology significantly reduces the need for manual inspections, minimizes human exposure to hazardous environments, and improves the precision and efficiency of pipeline maintenance operations. The development of pipe crawler robots represents a significant advancement in the field of robotics and infrastructure management, promising enhanced safety, reliability, and cost-effectiveness for industries reliant on extensive pipeline networks. Key words: inspection, autonomous, locomotion, robot, crawler., etc.

Vapor and Light Responsive Biocompatible Soft Actuator.

Bioinspired smart polymeric materials that undergo three-dimensional shape deformation in response to specific stimuli have gained significant attention in the field of soft robotics and intelligent devices. Despite the substantial advancements in soft robotics, there is a growing demand for the design of multistimuli-responsive soft actuators using a single layer of material due to its reduced complexity and ease of manufacturing and durability. Here, we report the actuation characteristics of a single-layer, dual-responsive soft actuator that overcomes the commonly encountered delamination issues often associated with bilayer systems by incorporating PEDOT:PSS with cassava starch. This soft actuator exhibits deformations in response to various solvent vapors, such as water, alcohol, and acetone. Remarkably, it demonstrates opposite deformations upon exposure to water and alcohol vapors. Additionally, the actuator responds to light triggers and folds upon exposure to sunlight and infrared light. The degree of folding can be precisely controlled by adjusting the intensity of the light source. Furthermore, the periodic geometric patterns imposed on the surface of the actuator provide an additional handle to control the bending axis. For proof of concept, we leverage the actuation capabilities of our actuator to showcase a range of potential applications, including its usage in wearable textiles, crawler robots, smart curtains, push-and-pull machines, and smart lifts.

An autonomous stair climbing method for the crawler robot based on a hybrid reinforcement learning controller

In response to problems in using deep reinforcement learning to perform the stair climbing task for the crawler robot, such as the lack of theoretical values for stair size range, the inaccurate force on the model using wheel to simulate track and difficulty in training, we propose an autonomous stair climbing method for the crawler robot based on a hybrid reinforcement learning controller. We propose a dynamics parameter settings method for fast simulation model by studying the distribution model of the ground pressure of the track, which improves the accuracy of the force on the fast simulation model in the stair climbing task. Our method calculates the climbing ability of the crawler robot by studying the kinematics and dynamics models of the real crawler robot in each stage of the stair climbing task, and combining with the control flow of the hybrid reinforcement learning controller. Further, we develop the training course of the hybrid reinforcement learning controller. The agent is trained in ROS-Gazebo. The course reduces the impact of poor trajectory on training, achieves higher success rates and faster convergence speed compared to random training, and effectively improves the generalization ability of the strategy.

Air-Coupled Ultrasonic Arrays for Assessment of Pipe Internal Geometry and Surface Condition.

This article explores what useful information can be retrieved from pipeline interiors using an air-coupled ultrasonic array. Experiments are performed using an array, custom array controller, and supporting electronics controlled by a Raspberry Pi 4, mounted on board a crawler robot. A 64-transducer 40-kHz array configuration is selected based on uniformity of imaging amplitude over the circumference of the pipe wall. Testing revealed joints between pipe sections could be imaged at high amplitude, and that angular displacement between sections produced a different response to a properly aligned joint, potentially enabling detection of faulty joints. The surface roughness of some pipes also provides enough backscatter to be imaged, which is useful for detecting regions of corrosion. It was also found that reflections from the pipe wall in the plane of the array allow imaging of the wall shape. This can indicate the presence of junctions, as well as detect ovality to within 1%. These in-plane wall reflections were also found to be a source of low-amplitude coherent noise throughout the imaging domain, which is of similar amplitude to small (< 10 mm) through-holes in the pipe wall.

Design of a Novel Attached Foot for Space Crawling Robot

Design of a Novel Attached Foot for Space Crawling Robot

An Amphibious Fully-Soft Centimeter-Scale Miniature Crawling Robot Powered by Electrohydraulic Fluid Kinetic Energy.

Miniature locomotion robots with the ability to navigate confined environments show great promise for a wide range of tasks, including search and rescue operations. Soft miniature locomotion robots, as a burgeoning field, have attracted significant research interest due to their exceptional terrain adaptability and safety features. Here, a fully-soft centimeter-scale miniature crawling robot directly powered by fluid kinetic energy generated by an electrohydraulic actuator is introduced. Through optimization of the operating voltage and design parameters, the average crawling velocity of the robot is dramatically enhanced, reaching 16mm s-1. The optimized robot weighs 6.3g and measures 5cm in length, 5cm in width, and 6mm in height. By combining two robots in parallel, the robot can achieve a turning rate of ≈3° s-1. Additionally, by reconfiguring the distribution of electrodes in the electrohydraulic actuator, the robot can achieve 2 degrees-of-freedom translational motion, improving its maneuverability in narrow spaces. Finally, the use of a soft water-proof skin is demonstrated for underwater locomotion and actuation. In comparison with other soft miniature crawling robots, this robot with full softness can achieve relatively high crawling velocity as well as increased robustness and recovery.

Research on Motion Control Optimization of Quadruped Crawling Robot for Continuous Slope

Background: In recent years, literature has suggested that quadruped crawling robots have been widely used in the field of reconnaissance on rugged mountain trails. Under the influence of gait and slope, the joint angle of the robot changes drastically when landing, resulting in the robot drop down from the slope. This has strict requirements for gait planning and gait control of quadruped crawling robots. Objective: The aim of this study is to set up a novel impedance controller based on gearshift integral PID to improve the stability of a quadruped crawling robot during climbing on a continuous slope. Methods: The three-dimensional model of quadruped crawling robot was established. Considering the characteristics of slope terrain, a slope diagonal gait design is proposed, and a gearshift integral PID impedance controller is designed for this gait. The impedance controller based on position PID, integral separation PID and gearshift integral PID is simulated by MATLAB, and the peak value of foot force is compared under ADAMS. Results: Overshoot and transient time of positional PID impedance controller was compared, integral separated PID impedance controller and gearshift integral PID impedance controller, the overshoot was reduced by 8.9% and the transient time was reduced by 20%. Finally, the position impedance controller that meets the requirements and import it into ADAMS to compare the peak foot force was selected, it reduced the foot-end contact force by 8.15%.The results show that the gearshift integral PID impedance control strategy is feasible. Conclusion: The Impedance controller based on gearshift integral PID can provide a reference for other impedance control strategies of quadruped crawling robots.

The Influence of Micro-Hexapod Walking-Induced Pose Changes on LiDAR-SLAM Mapping Performance.

Micro-hexapods, well-suited for navigating tight or uneven spaces and suitable for mass production, hold promise for exploration by robot groups, particularly in disaster scenarios. However, research on simultaneous localization and mapping (SLAM) for micro-hexapods has been lacking. Previous studies have not adequately addressed the development of SLAM systems considering changes in the body axis, and there is a lack of comparative evaluation with other movement mechanisms. This study aims to assess the influence of walking on SLAM capabilities in hexapod robots. Experiments were conducted using the same SLAM system and LiDAR on both a hexapod robot and crawler robot. The study compares map accuracy and LiDAR point cloud data through pattern matching. The experimental results reveal significant fluctuations in LiDAR point cloud data in hexapod robots due to changes in the body axis, leading to a decrease in map accuracy. In the future, the development of SLAM systems considering body axis changes is expected to be crucial for multi-legged robots like micro-hexapods. Therefore, we propose the implementation of a system that incorporates body axis changes during locomotion using inertial measurement units and similar sensors.

Influence on polygon effect with characteristic parameters of guide arc branch of the crawler robot

Influence on polygon effect with characteristic parameters of guide arc branch of the crawler robot

Biomimetic Crawling Robot Based on Dielectric Elastomer: Design, Modeling and Experiment

Biomimetic Crawling Robot Based on Dielectric Elastomer: Design, Modeling and Experiment

Structural Design and Obstacle-Crossing Performance Analysis of a Compact Anti-Terrorist Robot

In consideration of the risks faced by soldiers during anti-terrorism tasks, a compact anti-terrorism robot has been designed. This robot effectively combines detection and attack capabilities while maintaining a weight limit of 12kg. This paper provides a detailed description of the robot’s structural design and its obstacle-crossing action plan for climbing steps. From a kinematic perspective, it analyzes the relationship between the tracked robot’s structural dimensions and the height of steps. By utilizing Matlab, relationship diagrams are generated to determine the maximum step-climbing height by the tracked robot. Furthermore, Recurdyn software is employed to simulate obstacle crossings performed by this crawler robot in order to validate theoretical analysis through obtaining torque curves during movement. The results demonstrate that both structural dimensions and center-of-mass positioning significantly impact obstacle-crossing performance.

Research on Foothold Optimization of the Quadruped Crawling Robot based on Reinforcement Learning

Background:: Quadruped crawling robots will be faced with stability problems when walking on a raised slope. The stability of robot is affected by gait planning and selection of its foothold in this terrain. The slope reaction force on anterior and posterior legs is uneven. The selection strategy of its foothold should achieve good performance for the stability of the quadruped crawling robot. background: Quadruped crawling robots will be faced with stability problems when walking on the raised slope. The stability of robot is affected by gait planning and selection of its foothold in this terrain. The slope reaction force on anterior and posterior legs is uneven. The selection strategy of its foothold should achieve good performance for the stability of quadruped crawling robot. Objective:: Aimed at the uneven problem of slope reaction force on the anterior and posterior legs of the quadruped crawling robot when walking on the raised slope, a patent method for foothold optimization using reinforcement learning based on strategy search is proposed. objective: Aimed at the uneven problem of slope reaction force on anterior and posterior legs of the quadruped crawling robot when walking on the raised slope, a reinforcement learning method based on strategy search is adopted to select its foothold for quadruped crawling robot. Methods:: The kinematic model of the quadruped crawling robot is created in D-H coordinate method. According to the gait timing sequence method, the frame description of the quadruped crawling robot's gait on the slope is proposed. The fitting polynomial coefficients and fitting curves of all joints of the leg can be obtained by using the polynomial fitting calculation method. The reinforcement learning method based on Q-learning algorithm is proposed to find the optimal foothold by interacting with the slope environment. Comparative simulation and test of other gait and climbing slope gait, the climbing slope gait with and without the Q-learning algorithm is carried out by MATLAB platform. Results:: When the quadruped crawling robot adopts the reinforcement learning method based on Qlearning algorithm to select foothold, the robot posture curves are compared without optimization strategy. The result proves that the selection strategy of its foothold is valid. Conclusion:: The selection strategy of its foothold with reinforcement learning based on Q-learning algorithm can improve the stability of the quadruped crawling robot on the raised sloped. other: not have

Solid-State-LiDAR-Inertial-Visual Odometry and Mapping via Quadratic Motion Model and Reflectivity Information

This paper proposes a solid-state-LiDAR-inertial-visual fusion framework containing two subsystems: the solid-state-LiDAR-inertial odometry (SSLIO) subsystem and the visual-inertial odometry (VIO) subsystem. Our SSLIO subsystem has two novelties that enable it to handle drastic acceleration and angular velocity changes: (1) the quadratic motion model is adopted in the in-frame motion compensation step of the LiDAR feature points, and (2) the system has a weight function for each residual term to ensure consistency in geometry and reflectivity. The VIO subsystem renders the global map in addition to further optimizing the state output by the SSLIO. To save computing resources, we calibrate our VIO subsystem’s extrinsic parameter indirectly in advance, instead of using real-time estimation. We test the SSLIO subsystem using publicly available datasets and a steep ramp experiment, and show that our SSLIO exhibits better performance than the state-of-the-art LiDAR-inertial SLAM algorithm Point-LIO in terms of coping with strong vibrations transmitted to the sensors due to the violent motion of the crawler robot. Furthermore, we present several outdoor field experiments evaluating our framework. The results show that our proposed multi-sensor fusion framework can achieve good robustness, localization and mapping accuracy, as well as strong real-time performance.