Skid Steering Research Articles

Path tracking and energy efficiency coordination control strategy for skid-steering unmanned ground vehicle

The skid steering unmanned ground vehicle (SUGV) plays an important role in extremely harsh environments. Improving the autonomous control capability and energy efficiency of SUGV is urgently needed. This article presents a skid steering-based path tracking control strategy. In the upper controller, an improved model-free sliding mode controller (APMS) is used to calculate the yaw moment for tracking control. On the lower controller, the Snow Ablation Optimizer (SAO) is used to distribute the output torque of the drive motors, taking longitudinal force, yaw moment and energy consumption into account. Finally, the designed controller is validated through simulation under different operating conditions. The results show that the proposed coordination controller achieves good control performance, increases energy efficiency and at the same time ensures tracking accuracy.

Automatic determination of directional stability parameters of an electric vehicle with a two-motor scheme as part of the torque distribution controller

In case if the front and rear axle of the electric vehicle are not mechanically linked, the presence of automatic torque distribution to the axles or wheels becomes not only an addition to increase the level of consumer properties, but also a necessity. A method for determining the directional stability condition of an electric four-wheel drive vehicle is developed as part of the research by comparing the target and measured yaw rate, and is based on the formulated conditions of drift, skid, and counter steer registration. A method for detecting slipping of the driving wheels of an electric vehicle with a dual-motor scheme is developed, which is based on comparing the target and measured velocity differences of the front and rear axle and includes an auto oscillation detection function. A method for determining the target front and rear axle speed difference in a corner is described. Based on the tests performed, it is concluded that the proposed methods are applicable to the active torque distribution function between the axles of an all-wheel drive electric vehicle being developed by the authors of the paper, which provides improved directional stability and controllability, and counteracts slipping of the drive wheels.

Dynamics of tracked vehicles during nonuniform turning on level terrain and on slopes

This paper presents a detailed kinematic and dynamic model of nonuniform skid steering for tracked vehicles on level terrain and uniform skid steering slopes. The objective is to find the required forces applied on both tracks to achieve the desired turning, aiding in determining the needed engine power for effective turning operation. The vehicle kinematics during turning is presented, followed by a complete dynamic analysis that considers the effect of centrifugal and inertia forces, as well as adhesion with the ground. The dynamic analysis of turning on slopes is developed, where the cases of turning while moving uphill and downhill are considered. Moreover, simulation analysis using MATLAB model is conducted to investigate the main turning characteristics on both level terrain and slopes. The model can accurately predict the required forces on both tracks for effective turning, and can aid in the design of more efficient tracked vehicles. Generally, the findings of this study can inform the design of more efficient tracked vehicles by providing insights into the needed driving forces and the required power to achieve the desired radius of turning at a specific vehicle speed.

An Integrated Route and Path Planning Strategy for Skid–Steer Mobile Robots in Assisted Harvesting Tasks with Terrain Traversability Constraints

This article presents a combined route and path planning strategy to guide Skid–Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: (i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity; and (ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrate the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

Analysis of the PID Controller Parameters for A Surface Mobility Platform Mobile Robot

Surface mobility control is a fundamental challenge in robotics, and its applications range from autonomous vehicles to industrial automation. The main aim of the paper is to analyze the PID controller parameters for the speed control of a surface mobility platform mobile robot. MATLAB simulation toolbox and mathematical model of the DC motor are used to find the optimal PID controller parameters to complete the DC motor speed control system. For the SMP motion control system, the mobile robot kinematic model is supported as a differential drive system. In this paper, the PID controller parameters for the DC motor control system are analyzed with simulation results using various KP, KI, KD gains. The experimental results of the SMP mobile robot with optimal PID controller parameters are analyzed by driving on the rough, slope and even terrains. According to simulation results and experimental tests, the proposed system effectively controls the speed of the SMP mobile robot, demonstrating satisfactory performance in settling time, rise time, and system overshoot. Among PI and PID controllers, the designed PID controller can quickly control to reach the desired DC motor speed. Using the optimal PID coefficient parameters, all motors reached their desired speed in 0.12 seconds during simulations. In the experimental tests on various terrain (even, slope and rough), all motors achieved their desired speed simultaneously within 25 seconds.Keywords: Differential drive, PID controller, motion trajectory, real-time speed control. skid steering, SMP mobile robot, surface mobility control

Enhancing high-speed steering stability of wheel-legged vehicles by active roll control

Wheel-legged vehicles (WLVs) combine the speed of wheels with the active control of legs to traverse challenging terrain, which presents a new development possibility for enhancing the system’s mobility and stability. Most of the existing studies mainly focus on the stability of low-speed trajectory optimization or obstacle-surmounting by hybrid walking-driving. Without considering the stability of high-speed driving. To enhance the vehicle stability at high-speed steering, with the additional roll moment generated by the active roll motion taken into account, a 15-degree-of-freedom nonlinear yaw-roll coupled vehicle model is developed. Specifically, a fusion dynamic stability factor for skid steering is presented as the rollover threshold to determine the three-dimensional stability region of longitudinal speed, yaw rate and roll angle, based on which the vehicle’s ideal roll angle is obtained. Subsequently, a hierarchical parallel control scheme is proposed to decouple the yaw and roll motions of the wheel-legged vehicle. The fusion dynamic stability factor is regarded as the switching threshold of the upper-level controller, while the lower-level controller adopts the linear quadratic regulator and the sliding mode control to actively control additional roll moment and direct yaw moment, respectively. Furthermore, the studies for the dynamic model and the proposed controller are conducted through vehicle tests. Corresponding test results validate the advantages of the proposed control scheme over conventional schemes without active roll control, in which vehicle stability is effectively improved, thereby preventing vehicle rollover in the case of high-speed steering.

Extremum seeking control for the trajectory tracking of a skid steering vehicle via averaged sub-gradient integral sliding-mode theory

This study introduces the development of a novel extremum-seeking controller designed to stabilize the tracking trajectory of a fully actuated four-wheeled skid steering vehicle. The controller design employs a class of averaged sub-gradient optimization strategies for a suitable convex function that depends on the enforced tracking trajectory achieved through an integral sliding mode implementation. The application of this controller necessitates a nonlinear coordinate transformation of the skid steering vehicle dynamics, resulting in a perturbed multi-input–multi-output linear system. Using the proposed controller, a multidimensional sliding surface remains remarkably stable despite tracking errors. The surface design defines a manifold that aligns with the sub-gradient of a convex function, contingent upon the integral of the tracking error. This connection establishes a link between the extremum-seeking problem and the sliding mode control design. Employing the cascade design strategy, commonly referred to as backstepping, enables the calculation of torques for the four wheels of the mobile vehicle using a sequence of auxiliary sliding surfaces, each with its corresponding complementary function for every stage. The dynamic formulation for the wheel torques is derived from the integral sliding mode methodology. A series of numerical evaluations are conducted to assess the controller’s effectiveness in terms of functional performance. A comparison between the control action based on sliding mode and the traditional state feedback formulation validates the efficacy of the proposed design. This comparison demonstrates advancements in robustness in the face of modeling uncertainties and optimization of the performance function, which are theoretically supported by the suggested control design. Implementing the proposed controller in an experimental platform for a wheeled skid steering vehicle reaffirms the control design methodology presented in this study. This platform includes the application of an image processing algorithm to determine the non-inertial position of the autonomous vehicle using integral sliding mode control. This information completes the necessary data for implementing the on-site version of the proposed controller.

Controlling wheel loader motion along a desired trajectory

Problem. Rigid-frame skid steer front loaders are popular material-handling machines widely used in various industries. However, such loaders experience frequent breakdowns due to high dynamic loads; they are often subjected to intensive tyre wear and excessive fuel consumption. Frequently, these issues arise from the improper actions of an operator. Given the labour intensity of the workflow, an operator, regardless of qualification, cannot ensure optimal loader control at an acceptable speed for a long time. In addition, an operator usually works in harsh environments with a high risk of injury, e.g. due to loss of stability. Manual control of loaders also limits the use of these machines in places that are dangerous for humans, for example, during the response to disasters. The solution to these issues is to automate the loader and exclude the operator from the machine work. One of the tasks of loaders automation is to ensure their movement along a given trajectory from the face to the place of unloading the material and back in the opposite direction. Goal. This work aims to increase the productivity and energy efficiency of a rigid-frame skid steer loader by ensuring its following along a given trajectory. Methodology. Based on the kinematics model of the loader, a two-loop control system for motion along a desired trajectory is designed. The control system combines feedforward and feedback loops. The feed-forward control is based on the desired speeds and accelerations. The closed loop is a state controller that uses the loader distance from the desired trajectory at a given time and the course angle as the state variables. Results. According to the simulation results, the proposed two-loop control system ensures the movement of the loader along a desired trajectory with an accuracy of up to 0.3 m. Originality. Further development of the up-to-date control theory was achieved by applying it to a new object, namely a skid steer front loader with a rigid frame. Practical value. The implementation of the proposed control system will increase the productivity of the loader, as well as reduce the number of accidents at construction sites.

Aerial online mapping on‐board system by real‐time object detection for UGV path generation in unstructured outdoor environments

AbstractAn optimal path provides efficient operation of unmanned ground vehicles (UGVs) for many kinds of tasks such as transportation, exploration, surveillance, and search and rescue in unstructured areas that include various unexpected obstacles. Various onboard sensors such as LiDAR, radar, sonar, and cameras are used to detect obstacles around the UGVs. However, their range of view is often limited by movable obstacles or barriers, resulting in inefficient path generation. Here, we present the aerial online mapping system to generate an efficient path for a UGV on a two‐dimensional map. The map is updated by projecting obstacles detected in the aerial images taken by an unmanned aerial vehicle through an object detector based on a conventional convolutional neural network. The proposed system is implemented in real‐time by a skid steering ground vehicle and a quadcopter with relatively small, low‐cost embedded systems. The frameworks and each module of the systems are given in detail to evaluate the performance. The system is also demonstrated in unstructured outdoor environments such as in a football field and a park with unreliable communication links. The results show that the aerial online mapping is effective in path generation for autonomous UGVs in real environments.

Energy efficient path planning for autonomous ground vehicles with ackermann steering

The autonomous ground vehicles have attracted a great deal of attention as viable solutions to a wide variety of military and civilian applications. However, the energy consumption plays a major role in the navigation of autonomous ground vehicles in challenging environments, especially if they are left to operate unattended under limited on-board power, such as planetary exploration, border patrol, etc. The autonomous ground vehicles are expected to perform more tasks more efficiently with limited power in these scenarios. Although plenty of research has developed an effective methodology for generating dynamically feasible and energy efficient trajectories for skid steering or differential steering vehicles, few studies on path planning for ackermann steering autonomous ground vehicles are available. In this study, an energy efficient path planning method with guarantee on completeness is proposed for autonomous ground vehicle with ackermann steering which is based on A∗ search algorithm. Firstly, the energy cost model is established for the autonomous ground vehicle using its kinematic constraints. Then, given the start and goal states, the energy-aware motion primitives are generated offline using the energy cost model to calculate the cost of each primary trajectory. Lastly, the energy efficient path planner is proposed and the analysis for completeness properties is given. The effectiveness of the proposed energy efficient path planner is verified by simulation over 150 randomly generated maps and real vehicle tests. The results show that a small increase in the distance of a path over the distance optimal path can result in a reduction of energy cost by nearly 26.9% in simulation and 21.09% in real test scenario for autonomous ground vehicles with ackermann steering.

Online Fault Detection for Four Wheeled Skid Steered UGV Using Neural Network

This paper proposes a neural network-based actuator fault detection scheme for four-wheeled skid-steered unmanned ground vehicles (UGV). The neural network approach is first validated on vehicle dynamics simulations. Then, it is tailored for the experimental setup. Experiments involve a motion tracking system, Husarion Rosbot 2.0 UGV with associated network control systems. For experimental work, the disturbance is intentionally induced by augmenting wheels with a bump. Network size optimization is also carried out so that computing resource is saved without degrading detecting accuracy too much. The resulting network exhibit fault detection and isolation accuracy over 97% of the test data. A scenario is experimentally illustrated where a fault occurs, is detected, and tracking control is modified to continue operation in the presence of an actuator fault.

Deep Reinforcement Learning for Autonomous Dynamic Skid Steer Vehicle Trajectory Tracking

Designing controllers for skid-steered wheeled robots is complex due to the interaction of the tires with the ground and wheel slip due to the skid-steer driving mechanism, leading to nonlinear dynamics. Due to the recent success of reinforcement learning algorithms for mobile robot control, the Deep Deterministic Policy Gradients (DDPG) was successfully implemented and an algorithm was designed for continuous control problems. The complex dynamics of the vehicle model were dealt with and the advantages of deep neural networks were leveraged for their generalizability. Reinforcement learning was used to gather information and train the agent in an unsupervised manner. The performance of the trained policy on the six degrees of freedom dynamic model simulation was demonstrated with ground force interactions. The system met the requirement to stay within the distance of half the vehicle width from reference paths.

Injuries and Fatalities Related to Skid Steers: 2015–2020

Skid steers are versatile self-propelled machines that are regularly used in a variety of recreational applications and occupational industries. They can be hazardous for both operators and bystanders. The purpose of this paper is to describe patterns of skid steer injuries in the US from 2015 to 2020. Data were obtained from Occupational Safety and Health Administration (OSHA) accident reports and the severe injury database. Agriculture-related incidents were obtained from AgInjuryNews. The study identified 312 skid steer-related injuries (2015–2020) in OSHA, with an additional 68 agricultural injuries identified using AIN. Construction, administrative and waste management, and agriculture industries were the top three industries with the highest number of injuries. Bystander workers experienced a higher number of injuries than operators. Contact with the machine was the most prevalent and more fatal than the other injury events. Agricultural skid steer injuries involved a broad age range of victims, from very young children to adults. These findings emphasize the need for improved safety engineering and clear safety guidelines for skid steer operators and those who are around skid steers. With the increased prevalence of skid steers across industries, it is imperative to have cohesive and comprehensive safety regulations, guidelines, and policy enforcement.

Multi-Trajectory Approach for a Generic Coordination Paradigm of Wheeled Mobile Manipulators

This letter presents a generic coordination approach for the control of mobile manipulators. It is based on an external coupled coordination and exploits a multi-trajectory following approach. A coordination stage provides optimal offsets with respect to system sub-parts reference trajectories that minimize a cost function to manage the system redundancies. In order to face the diversity of tasks to be performed by the robotic platform, the cost function is composed of different criteria that can be adapted, pending on the mission assigned to the robot. A demonstration of its generic properties is proposed on different mobile manipulator structures in simulations. Finally, the effectiveness of the proposed method is evaluated through full-scale experiments with a single-arm skid steering mobile manipulator.

Fault-Tolerant Control of Skid Steering Vehicles Based on Meta-Reinforcement Learning with Situation Embedding

Meta-reinforcement learning (meta-RL), used in the fault-tolerant control (FTC) problem, learns a meta-trained model from a set of fault situations that have a high-level similarity. However, in the real world, skid-steering vehicles might experience different types of fault situations. The use of a single initial meta-trained model limits the ability to learn different types of fault situations that do not possess a strong similarity. In this paper, we propose a novel FTC method to mitigate this limitation, by meta-training multiple initial meta-trained models and selecting the most suitable model to adapt to the fault situation. The proposed FTC method is based on the meta deep deterministic policy gradient (meta-DDPG) algorithm, which includes an offline stage and an online stage. In the offline stage, we first train multiple meta-trained models corresponding to different types of fault situations, and then a situation embedding model is trained with the state-transition data generated from meta-trained models. In the online stage, the most suitable meta-trained model is selected to adapt to the current fault situation. The simulation results demonstrate that the proposed FTC method allows skid-steering vehicles to adapt to different types of fault situations stably, while requiring significantly fewer fine-tuning steps than the baseline.

Metalearning-Based Fault-Tolerant Control for Skid Steering Vehicles under Actuator Fault Conditions.

Using reinforcement learning (RL) for torque distribution of skid steering vehicles has attracted increasing attention recently. Various RL-based torque distribution methods have been proposed to deal with this classical vehicle control problem, achieving a better performance than traditional control methods. However, most RL-based methods focus only on improving the performance of skid steering vehicles, while actuator faults that may lead to unsafe conditions or catastrophic events are frequently omitted in existing control schemes. This study proposes a meta-RL-based fault-tolerant control (FTC) method to improve the tracking performance of vehicles in the case of actuator faults. Based on meta deep deterministic policy gradient (meta-DDPG), the proposed FTC method has a representative gradient-based metalearning algorithm workflow, which includes an offline stage and an online stage. In the offline stage, an experience replay buffer with various actuator faults is constructed to provide data for training the metatraining model; then, the metatrained model is used to develop an online meta-RL update method to quickly adapt its control policy to actuator fault conditions. Simulations of four scenarios demonstrate that the proposed FTC method can achieve a high performance and adapt to actuator fault conditions stably.

A Skid-Steering Method for Path-Following Control of Distributed-Drive Articulated Heavy Vehicles

Distributed-drive articulated heavy vehicles (DAHVs) have separate front and rear sections and require a complex hydraulic steering system to achieve the steering process, which poses considerable challenges in obtaining better steering characteristics and achieving path-following control. In this paper, the distributed-drive characteristic of DAHVs is used to develop a novel skid-steering method (SSM) in which the hydraulic steering method (HSM) is replaced with a system that differentially controls the driving wheels to improve vehicle steering performance and path following control accuracy. Three main contributions are made: 1) The novel SSM with direct yaw moment that is used to be the sole power source during steering process of DAHVs is designed to replace the conventional HSM. 2) The idea of SSM by yaw rate control of one vehicle section to achieve the steering process for DAHVs is proposed firstly, which can solve the complex problem of requiring multiple control parameters due to the separate vehicle sections of DAHVs. 3) A layered control method is implemented to improve the robustness of the control system, which is composed of an upper path following controller and a lower skid steering controller combined with a double sliding mode control technique. The system’s stability and robustness are proven by the Lyapunov approach. A co-simulation model verified by field tests is used to demonstrate the feasibility and effectiveness of the proposed control method. The results of this study provide a new way to improve the intelligence of DAHVs.

Storing Peanuts in Grain Bags

HighlightsExisting bag loading equipment may be used to load both in-shell and shelled oil stock peanuts.Grain bags can be loaded at 1.2 t/m of in-shell peanuts and 2.3 t/m of shelled oil stock peanuts.Existing extraction equipment requires modification to unload shelled oil stock peanuts due to poor flow characteristics.Grain bags not suitable for storing in-shell peanuts due to significant moisture migration and quality reduction under typical Georgia conditions.Abstract.Edible grade farmers’ stock peanuts and shelled oil stock peanuts were stored in hermetically sealed silo or grain bags to determine their suitability for short-term storage. The objectives of the study were to evaluate equipment for loading and unloading the grain bags, the capacity of the grain bags, and the changes in quality. In May 2015, approximately 90 Mg of farmers’ stock (in-shell) peanuts from the 2014 crop were unloaded from a commercial warehouse, transported to Dawson, Georgia, and loaded into two 2.7 m diameter grain bags. Similarly, 85 Mg of shelled oil stock peanuts were loaded into two 2.7 m diameter grain bags. Farmers’ stock bags were unloaded after 30 and 60-d storage. A vacuum extractor and a skid steer loader were used due to wet peanuts in the top of the bag. Both oil stock bags were unloaded after 60-d storage. A skid steer loader was used to unload the oil stock bags because shelled oil stock peanuts did not flow adequately to use the conventional bag extraction equipment. Oxygen content in the farmers’ stock peanuts decreased from ambient levels (21%) to an average of 8.6% after 15-d storage. After 20-d storage, the oxygen content in the oil stock had decreased to 14%. A layer of high moisture peanuts due to moisture migration and subsequent condensation in the top of both of the farmers’ stock bags resulted in the peanuts being unsuitable for human consumption and reduced the value from $342/Mg to approximately $125/Mg for oil stock, a 63% reduction in value. No moisture problems were observed in the oil stock bags when they were unloaded. Based on these studies, sealed grain bags would be unsuitable for temporarily storing farmers’ stock peanuts under typical Georgia conditions. Sealed grain bags could possibly be used to store oil stock peanuts for 60 d, but suitable unloading equipment would have to be found or developed. Keywords: Grain bag, Groundnut, Handling, Hermetic, Peanut, Silo bag, Storage.

Path Tracking of a Four-Wheel Independently Driven Skid Steer Robotic Vehicle Through a Cascaded NTSM-PID Control Method

Four-wheel independently driven skid steer robotic vehicles (IDSSRVs) have been widely applied in many fields. However, limited by small size and low power consumption, many sensors and high-performance processors cannot be equipped into four-wheel IDSSRVs, which makes path tracking more complex. The nonsingular terminal sliding mode (NTSM) is a good choice for small robotic vehicles because of its strong robustness, fast convergence, and low complexity. However, the performance of the NTSM is easily affected by vehicular weight and road friction because a four-wheel IDSSRV has no steering devices and its driving behavior is completed by adjusting the velocity of the four wheels based on the wheel–ground interaction. Furthermore, a minor instability caused by the output difference of the motors can bring extra torque on the vehicle and ultimately lead to a tracking deviation for the NTSM controller. To resolve these problems, a dynamic model of a four-wheel IDSSRV is analyzed first. Subsequently, a cascaded NTSM-proportional–integral–derivative (PID) method is proposed, in which a conversion function based on compensating the sideslip angle is raised to improve the NTSM controller performance of antidisturbance and tracking accuracy with the limitations of the sensors and processors, and a joint PID controller simultaneously optimizing the motor output error and vehicular yaw error is designed to eliminate the imbalance of motor output and to reduce the deviation of the NTSM controller. Finally, comparative experiments are conducted, and the results highlight the benefits of the proposed approach by reducing the tracking error by approximately 80% compared with the dynamic model predictive control (MPC) method and reducing the tracking error by over 30% compared with the pure NTSM method.

저속 무한궤도 차량의 클러치/브레이크 방식 조향 제어에 관한 연구

Various steering systems are used for agricultural automation especially ridge planting machines. The flexible continuous tracks with skid steering are suitable solutions. Considering the size of the machines, the tracks must be controlled using the clutch/brake steering system, which causes discontinuity. In order to use autonomous steering, the fast on-off control on the clutch should be applied. Knowing the turning radius during steering by the on-off operation is essential, which can be obtained with the detailed system simulations by Amesim. It has been found that the on-off frequencies and the turning radius has linear relationship in most usable high frequency spectrum. Thus, the fast on-off control of clutch, as an autonomous steering assistance system, makes it easier to steer tracked vehicles with suitable sensors.