Intelligent unmanned decision obstacle crossing mobile platform based on state
By combining the design of deformable wheel set and McNum wheel, combined with fuzzy logic and SLAM intelligent perception, the unmanned platform is able to efficiently move and work on multiple terrain, solving the problem of insufficient mobility and compactness, and adapting to various terrain conditions.
Patent Information
- Application Number
- CN202510669901.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-23
- Publication Date
- 2025-08-29
AI Technical Summary
The existing unmanned obstacle-blocking platforms have shortcomings in terms of mobility and compactness, making it difficult to move and operate efficiently in a variety of terrain environments, especially under complex terrain conditions such as wading and climbing.
The combination of deformable wheel sets and steering McNum wheels is adopted, combining fuzzy logic and SLAM intelligent perception mapping decision-making methods to achieve intelligent decision-making of the platform and multiple terrain adaptability.
It improves the adaptability and mobility of the platform on a variety of terrain, and can move and operate efficiently in flat roads, rugged terrain and wading environments to meet the needs of emergency rescue and special operations.
Smart Images
Figure CN120552986A_ABST
Abstract
Description
Technical Field
[0001] The present invention discloses a state-based intelligent unmanned decision-making obstacle-crossing mobile platform, belonging to the field of obstacle-crossing mobile platforms. Background Art
[0002] There are many ideas for the design of unmanned obstacle crossing platforms at home and abroad. Specifically, they can be divided into the following three design options:
[0003] 1. Swing arm wheel design
[0004] The floating wheel + swing arm type is widely used. It has the characteristics of simple structure and good obstacle-crossing performance; however, its maneuverability is slightly poor and it is not compact enough.
[0005] 2. Swing arm track design
[0006] The crawler + swing arm type is also widely used. The crawler itself has good ground adaptability, and the addition of the swing arm can increase its obstacle clearance height; however, its maneuverability is slightly poor and the structure is often bulky.
[0007] 3. Swing arm bionic design
[0008] Incorporating bionic principles and referencing the gait of multi-legged animals, the design of a mobile platform achieves obstacle surmounting. This design often employs a "legs-wheels-shoes" approach. This provides strong obstacle-surmounting capabilities and improved maneuverability, but the structure is complex.
[0009] With comprehensive reference to the above designs, focusing on improving the advantages of the mobile platform such as mobility and compactness, and taking into account the ideas of intelligent unmanned decision-making, a state-based intelligent unmanned decision-making obstacle-crossing mobile platform is now designed. Summary of the Invention
[0010] The present invention aims to provide a state-based intelligent unmanned obstacle-crossing mobile platform and obstacle-crossing method. The mobile platform can adapt to various terrains and perform maneuvering operations in various terrain environments. It can move, cross obstacles, and wade through water, thereby performing obstacle-crossing tasks in various terrain conditions. Various terrain conditions include flat roads, rough ground, and wading environments. Maneuvering tasks include emergency rescue and special operations.
[0011] The purpose of the present invention is achieved through the following technical solutions:
[0012] The present invention discloses a state-based intelligent unmanned decision-making obstacle-crossing mobile platform, which includes three parts: a vehicle frame, a deformable wheel set and a control part.
[0013] The frame is equipped with multifunctional slots. Motor mounts are located at the four corners of the frame for easy connection to the main drive motor. The control unit is located on the frame of the unmanned platform and is used for controlling and powering the platform.
[0014] The deformable wheel assembly consists of four independent deformable wheels. These wheels are composed of a drive unit, a deformable unit, and a translation unit. The drive unit is the main drive motor. The deformable unit includes an inner wheel frame, an outer wheel frame, a deformable motor, a deformable transmission worm gear, a deformable hollow shaft, a center deformable gear, and a deformable half gear. The translation unit includes the half gear track, Mecanum wheel rollers, and a Mecanum wheel steering mechanism.
[0015] Furthermore, the deformation part includes: an inner wheel frame, an outer wheel frame, a deformation motor, a deformation transmission worm gear, a deformation hollow shaft, a center deformation gear and a deformation half gear.
[0016] The solid shaft is fixedly connected to the inner and outer wheel frames. Its other end is connected to the drive shaft via a coupling, driving the entire deformation wheel through the main drive motor. A deformable hollow shaft fits over the solid shaft, preventing interference between the two. One end of the deformable hollow shaft is fixedly connected to the deformable drive worm gear, while the other end is connected to the center deformable gear. The center deformable gear is located between the inner and outer wheel frames. Three deformable half gears mesh with the center deformable gear. The deformable motor is evenly fixed to the inner wheel frame and meshes with the deformable drive worm gear via a worm.
[0017] Furthermore, the translation portion includes a half-gear track, a Mecanum wheel roller, and a Mecanum wheel steering mechanism.
[0018] The half-gear track is fixed to the outside of the deformed half-gear. The Mecanum wheel steering mechanism consists of a Mecanum wheel steering 1 / 3 rack, a steering motor, and a Mecanum wheel frame. The Mecanum wheel frame is a disc structure with a rack-shaped edge, which meshes with the Mecanum wheel steering 1 / 3 rack via the rack. The steering motor is fixed to the Mecanum wheel frame and fixedly connected to the half-gear track. The Mecanum wheel roller is hinged to the outside of the Mecanum wheel frame.
[0019] A method for controlling a state-based intelligent unmanned obstacle-crossing mobile platform. The platform is equipped with sensors that monitor the status of obstacles ahead in real time. A method combining fuzzy logic and SLAM-based intelligent perception and mapping is used to make intelligent decisions about obstacle crossing, resulting in a driving behavior that reflects the current state of the unmanned platform.
[0020] Furthermore, the unmanned platform uses a method that combines fuzzy logic and SLAM-based intelligent perception mapping. The specific implementation method is as follows:
[0021] SLAM intelligent sensing builds a spatial map and performs path planning to determine the route. Cameras and radar sensors monitor the distance x and height h of obstacles in real time. The measured sensor data is converted into fuzzy sets, which is the process of converting data into fuzzy linguistic variables in fuzzy logic control.
[0022] The definition of fuzzy linguistic variables has two layers: the first layer is the decision layer for the “obstacle crossing”, “advance” and “obstacle avoidance” behaviors; the second layer is the decision layer for the “obstacle crossing” and “obstacle avoidance” actions.
[0023] Furthermore, the first-layer behavior decision-making method is as follows: For the unmanned platform's obstacle crossing limit, the obstacle height h must be less than the maximum radius R after deformation. The system determines whether the obstacle height meets the obstacle crossing condition and records the distance x. The radius of the deformed wheel in the wheeled state is r. Based on the obstacle height h, one of the following behaviors is executed.
[0024] Behavior 1: Low obstacle, forward behavior.
[0025] Behavior 2: Ability to climb over obstacles, obstacle-crossing behavior.
[0026] Behavior 3: Do not cross obstacles and avoid obstacles.
[0027] The low obstacle: when h=0, the membership is 1, and as h increases, the membership decreases.
[0028]
[0029] Symbol explanation μ L is the membership degree of low obstacles.
[0030] The surmountable obstacle: when h=r, the membership is 0, and as h increases, it becomes 1 when it reaches 0.5(R+r), and then the membership decreases, and the membership is 0 when it reaches R.
[0031]
[0032] Symbol explanation μ M is the membership degree of low obstacles.
[0033] The insurmountable obstacle: when h=R, the membership is 0, and the larger h is, the larger the membership is. When it reaches 2R, the membership is 1 and remains.
[0034]
[0035] Symbol explanation μ H is the membership degree of low obstacles.
[0036] Through μ L 、μ M or μ H Decision-making behavior.
[0037] Furthermore, the method for making action decisions at the second layer is to determine the action under known behavior according to the distance x measured from the platform to the obstacle.
[0038] When the forward behavior is determined, that is, behavior 1, the deceleration distance from the obstacle is defined as Y, which is given as follows:
[0039] rule:
[0040] 1. Define “near” and move forward at a slower speed.
[0041] 2. Define “far” and keep moving forward.
[0042] Define "near" as follows: if x <= Y, the membership is 1 when x = 0, and the membership gradually decreases as the distance increases.
[0043]
[0044] Define "far" as follows: if x>=Y, the membership is 0 when x=Y, becomes 1 when the distance increases to 2Y, and remains unchanged thereafter.
[0045]
[0046] When the obstacle crossing behavior is determined, that is, behavior 2, the limit closest deformation distance can be designed as l, and the obstacle crossing action distance X is defined. The following rules are given:
[0047] 1. Define "near" and slow down to perform deformation action.
[0048] 2. Define “far” and keep moving forward.
[0049] The definition of "close" is that if l<=x<=X, the membership is 1 when x=l, and the membership gradually decreases as the distance increases.
[0050]
[0051] Define "far" as follows: if x>=X, the membership is 0 when x=X, becomes 1 when the distance increases to 2X, and remains unchanged thereafter.
[0052]
[0053] When determining the obstacle avoidance behavior, that is, behavior 3, the distance to avoid the obstacle is defined as Z, which is given as follows:
[0054] rule:
[0055] 1. Definition of “near”: using a Mecanum wheel to move sideways in place.
[0056] 2. Define "far" and use the Mecanum wheel for small-angle steering.
[0057] The definition of "close" is: if x <= Z, the membership is 1 when x = 0, and the membership gradually decreases as the distance increases.
[0058]
[0059] Define "far" as follows: if x>=Z, the membership is 0 when x=Z, and becomes 1 when the distance increases to 2Z, and then remains unchanged.
[0060]
[0061] In the stair climbing state, the deformable wheel is always in the deformed and open state, performing the stair climbing action without considering the steering and translation actions.
[0062] A method for moving and overcoming obstacles using a state-based intelligent unmanned decision-making obstacle-crossing mobile platform is implemented as follows:
[0063] When the platform is translating, that is, traveling on relatively flat ground, the deformable wheels are in a wheeled state. The Mecanum wheel steering rack engages the Mecanum wheel frame, causing the Mecanum wheel rollers to be oriented at 45 degrees, allowing for conventional Mecanum wheeled motion. The four wheels are positioned at the four corners of the frame, and the O-shaped Mecanum wheels are arranged so that the four wheels roll in the same direction, allowing the platform to move forward or reverse. When steering is required, the four wheels can rotate in different directions according to the required steering parameters, allowing the Mecanum wheels to be used for curved driving in different directions.
[0064] When the mobile platform is navigating obstacles or wading through water, such as climbing stairs or over a body of water, the deformable motor drives the worm, which drives the deformable transmission worm gear to rotate a certain angle. This drives the deformable hollow shaft relative to the solid shaft, thereby driving the central deformable gear to engage the three deformable half gears, forming a swing arm position. The deformable half gears are symmetrical and can also be deployed in reverse, allowing the mobile platform to be deployed backwards to climb stairs. At the same time, the Mecanum wheel rollers are deflected to 0° (the Mecanum wheel roller axis is parallel to the solid shaft), facilitating obstacle traversal and underwater propulsion.
[0065] Beneficial effects:
[0066] 1. The present invention discloses a state-based intelligent unmanned decision-making obstacle-crossing mobile platform and obstacle-crossing method. This platform utilizes a four-wheeled unmanned platform design that combines a deformable wheel set with a steerable Mecanum wheel and is compatible with a plug-in tool library. Compared to traditional single-operation-mode unmanned platforms, this platform can be used for multiple operating conditions, including obstacle crossing, wading, and moving on flat ground. It can adapt to various terrains and perform a variety of operations, thus improving its adaptability.
[0067] 2. The present invention discloses a state-based intelligent unmanned decision-making obstacle-crossing mobile platform and obstacle-crossing method. This platform utilizes a gear meshing wheel deformation method that can be deformed and expanded in both forward and reverse directions. Compared to traditional Mecanum wheel trolleys or swing-arm obstacle-crossing vehicles, the worm gear drives the central gear meshing half gear, which can be expanded in both forward and reverse directions. Furthermore, the mobile obstacle-crossing structure with a Mecanum wheel rotor that can change direction can be maneuvered in a small space and is more compact, thereby improving maneuverability.
[0068] 3. The present invention discloses a state-based intelligent unmanned decision-making obstacle-crossing mobile platform and obstacle-crossing method, which adopts task planning based on the above-mentioned different environmental states (obstacle crossing, climbing and translation) and an intelligent decision-making method for behavioral actions using SLAM and fuzzy logic control. Compared with other decision-making methods, it can better match the operational requirements of various situations according to the structural characteristics of the unmanned platform. BRIEF DESCRIPTION OF THE DRAWINGS
[0069] Figure 1 Schematic diagram of a state-based intelligent unmanned decision-making obstacle-crossing mobile platform of the present invention.
[0070] Figure 2 This is a schematic diagram of the obstacle-crossing mobile platform in its deformed wheeled state.
[0071] Figure 3 This is a schematic diagram of the obstacle-crossing mobile platform in its transformed wheel-leg state.
[0072] Figure 4 This is an explanatory diagram of the obstacle-crossing maneuvering platform.
[0073] Among them, 1 is the main drive motor, 2 is the coupling, 3 is the inner wheel frame, 4 is the Mecanum wheel steering 1 / 3 rack, 5 is the Mecanum wheel frame, 6 is the deformation motor, 7 is the worm, 8 is the deformation transmission worm gear, 9 is the steering motor, 10 is the Mecanum wheel roller, 11 is the center deformation gear, 12 is the deformation half gear, 13 is the solid shaft, 14 is the deformation hollow shaft, 15 is the half gear shoe, and 16 is the outer wheel frame.
[0074] Figure 5 This is a decision state diagram of a state-based intelligent unmanned decision-making obstacle-crossing mobile platform of the present invention. DETAILED DESCRIPTION
[0075] In order to better illustrate the purpose and advantages of the present invention, the invention is further described below with reference to the accompanying drawings and examples.
[0076] Example 1:
[0077] It is used for material transport and maintenance in a three-dimensional unmanned factory workshop. Figure 1 The unmanned platform uses sensors such as SLAM radar and cameras to build a map of the surrounding environment, and then can Figure 5 Decide on the current situation.
[0078] In a small space, the surrounding environment is judged as "insurmountable obstacles" through fuzzy logic, and "obstacle avoidance behavior" is performed, and it is defined as "far". Figure 2Mecanum wheels can be used for small-angle steering. The main drive motor 1 drives four deformable wheels, which utilize the characteristics of the Mecanum wheels for wheeled motion. The Mecanum wheel steering rack 4 engages the Mecanum wheel frame 5, causing the Mecanum wheel roller 10 to align at a 45-degree angle. The four wheels roll in the same direction, allowing the platform to move forward or reverse, or rotate in different directions according to the required steering parameters. The Mecanum wheels can be used to navigate curves in different directions. The unmanned platform can be equipped with a corresponding robotic arm for operation.
[0079] When the fuzzy logic determines that an obstacle can be climbed over, the obstacle climbing behavior is performed, such as Figure 3 The worm gear 8 can be transformed into a swing-arm leg-like state. The deformable motor 6 drives the worm 7 to mesh with the deformable transmission worm gear 8, which rotates through the deformable hollow shaft 14, driving the center deformable gear 11 to rotate. The meshed deformable half gears 12 are then deployed. If the obstacle height is 20 cm, the deformation angle is determined by the equivalent radius after deformation. If the equivalent radius is greater than 20 cm, the "obstacle-crossing behavior" can be performed. For each deformable wheel, there are three deformable half gears 12 driving the swing arm. For one of the half gear tracks 15, the steering motors 9 at both ends of the half gear track 15 drive the Mecanum wheel frames 5 at both ends of the half gear track 15 to rotate, which in turn meshes with the Mecanum wheel steering 1 / 3 rack 4. The inner and outer Mecanum wheel steering 1 / 3 racks 4 mesh with the middle Mecanum wheel frames 5 of the half gear track 15, so that all Mecanum wheel rollers 10 are synchronously oriented at 0° (the Mecanum wheel roller 10 axes are axially parallel to the solid shaft 13). Because the three half gears 12 are synchronously driven by the center deformable gear 11, the three swing arms deform synchronously.
[0080] Example 2:
[0081] The state-based intelligent unmanned decision-making obstacle-crossing mobile platform in Example 2 is the same as that in Example 1.
[0082] When conducting field special operations and exploration and rescue, Figure 1 The unmanned platform can be adjusted according to the environment Figure 5 Decision-making on the corresponding state, determine the appropriate deformation angle. When on a relatively flat ground, such as Figure 2 Perform wheeled sports; when climbing steep rock faces or high platforms, make the following decisions based on your understanding of the environment. Figure 3 When entering a wading area (water area), it can be used amphibiously. The Mecanum wheel frame 5 changes direction so that all Mecanum wheel rollers 10 are synchronously in a 0° direction (the axis of the Mecanum wheel roller 10 is parallel to the axis of the solid shaft 13). The four main drive motors 1 drive the four deformable wheels to rotate, which act as paddles to paddle forward. Like a "special forces soldier", the unmanned platform can adapt to various terrains and can carry corresponding tools to perform various complex operations.
[0083] The above specific description further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
Claims
1. A state-based intelligent unmanned decision-making obstacle-crossing mobile platform, characterized by: It consists of three parts: frame, deformable wheel set and control part; There are multifunctional slots on the frame; The four corners of the frame are equipped with motor racks for easy connection to the main drive motor; the control unit is placed on the frame of the unmanned platform and is used for the control and power supply of the unmanned platform; The deformation wheel set consists of four independent deformation wheels; The deformation wheel consists of a driving part, a deformation part and a translation part; The driving part is the main driving motor; the deformation part includes: inner wheel frame, outer wheel frame, deformation motor, deformation transmission worm gear, deformation hollow shaft, center deformation gear and deformation half gear; the translation part includes half gear track, Mecanum wheel roller and Mecanum wheel steering mechanism.
2. The state-based intelligent unmanned decision-making obstacle-crossing mobile platform according to claim 1, characterized in that: The deformation part includes: an inner wheel frame, an outer wheel frame, a deformation motor, a deformation transmission worm gear, a deformation hollow shaft, a center deformation gear and a deformation half gear; The solid shaft is fixedly connected to the inner wheel frame and the outer wheel frame, and the other end is connected to the shaft of the driving part through a coupling, and the overall rotation of the deformed wheel is driven by the main drive motor; the deformed hollow shaft is sleeved on the outside of the solid shaft, and the two do not interfere with each other; one end of the deformed hollow is fixedly connected to the deformed transmission worm gear, and the other end is connected to the center deformed gear; the center deformed gear is located between the inner wheel frame and the outer wheel frame; the three deformed half gears are meshed with the center deformed gear; the deformed motor is evenly fixed on the inner wheel frame, and is meshed with the deformed transmission worm gear through a worm.
3. The state-based intelligent unmanned decision-making obstacle-crossing mobile platform according to claim 1, characterized in that: The translation part includes a half gear shoe, a Mecanum wheel roller and a Mecanum wheel steering mechanism; The half gear shoe is fixed on the outside of the deformed half gear; the Mecanum wheel steering mechanism includes: a Mecanum wheel steering 1 / 3 rack, a steering motor and a Mecanum wheel frame; The mecanum wheel frame is a disc structure with a rack-shaped edge, which meshes with the mecanum wheel steering 1 / 3 rack through the rack. The steering motor is fixed to the mecanum wheel frame and fixedly connected to the half gear track. The mecanum wheel roller is hinged to the outside of the mecanum wheel frame.
4. The method for controlling the motorized platform to overcome obstacles according to claim 1, characterized in that: The unmanned platform is equipped with sensors that can monitor the status of obstacles ahead on the path in real time; a method combining fuzzy logic and SLAM-based intelligent perception mapping is used to make intelligent decisions on obstacle crossing and obtain the current driving behavior of the unmanned platform.
5. The method according to claim 4, wherein: The unmanned platform uses a method that combines fuzzy logic and SLAM-based intelligent perception mapping. The specific implementation method is as follows: SLAM intelligent perception is used to build a spatial map and perform path planning to determine the path. Cameras and radar sensors monitor the distance x and height h of obstacles in real time. The actual measured sensor data is converted into fuzzy sets, which means that in fuzzy logic control, the data needs to be converted into fuzzy language variables. As for the definition of fuzzy linguistic variables, there are two layers. The first layer is the decision-making layer for the "obstacle crossing", "advance" and "obstacle avoidance" behaviors; the second layer is the decision-making layer for the "obstacle crossing" and "obstacle avoidance" actions.
6. The method according to claim 5, wherein: The first-level behavior decision-making method is as follows: for the unmanned platform's obstacle crossing limit, the obstacle height h should be less than the maximum radius R after deformation; identify whether the obstacle height meets the obstacle crossing condition and record the distance x; the radius of the deformed wheel in the wheeled state is r; based on the obstacle height h, perform one of the following behaviors; Behavior 1: low obstacle, forward behavior; Behavior 2: can climb over obstacles, obstacle-crossing behavior; Behavior 3: Do not cross obstacles, obstacle avoidance behavior; The low obstacle: when h=0, the membership is 1, and as h increases, the membership decreases; Symbol explanation μ L is the membership degree of low obstacles; The surmountable obstacle: when h=r, the membership is 0, and as h increases, it becomes 1 when it reaches 0.5(R+r), and then the membership decreases, and the membership becomes 0 when it reaches R; Symbol explanation μ M is the membership degree of low obstacles; The insurmountable obstacle: when h=R, the membership is 0, the larger h is, the greater the membership is, and when it reaches 2R, the membership is 1 and remains; Symbol explanation μ H is the membership degree of low obstacles; Through μ L 、μ M or μ H Decision-making behavior.
7. The method according to claim 5, wherein: The second layer makes action decisions by determining the action based on the distance x measured from the platform to the obstacle and the known behavior; When the forward behavior is determined, that is, behavior 1, the deceleration distance from the obstacle is defined as Y, which is given as follows: rule:
1. Define "near" and slow down and move forward; 2. Define "far" and keep moving forward; Define "close", if x <= Y, the membership is 1 when x = 0, and the membership gradually decreases as the distance increases; Define "far" as follows: if x>=Y, the membership is 0 when x=Y, and becomes 1 when the distance increases to 2Y, and then remains unchanged; When the obstacle crossing behavior is determined, that is, behavior 2, the limit closest deformation distance can be designed as l, and the obstacle crossing action distance X is defined. The following rules are given:
1. Define "near" and decelerate to perform deformation action; 2. Define "far" and keep moving forward; The definition of "close" is: if l <= x <= X, the membership is 1 when x = l, and the membership gradually decreases as the distance increases; Define "far" as follows: if x>=X, the membership degree is 0 when x=X, and becomes 1 when the distance increases to 2X, and then remains unchanged; When determining the obstacle avoidance behavior, that is, behavior 3, the distance to avoid the obstacle is defined as Z, which is given as follows: rule:
1. Definition of "near" refers to using Mecanum wheels to move sideways in place; 2. Define "far" and use Mecanum wheels for small-angle steering; Define "close", if x <= Z, the membership is 1 when x = 0, and the membership gradually decreases as the distance increases; Define "far", if x>=Z, the membership is 0 when x=Z, and becomes 1 when the distance increases to 2Z, and then remains unchanged; In the stair climbing state, the deformable wheel is always in the deformed and open state, performing the stair climbing action without considering the steering and translation actions.
8. A method for moving and overcoming obstacles using the mobile platform as claimed in claim 1, 2 or 3, characterized in that: When the mobile platform is moving horizontally, that is, when traveling on a relatively flat ground, the deformed wheels are in a wheeled state, and the 1 / 3 rack meshes with the Mecanum wheel frame so that the Mecanum wheel rollers are in a 45° direction, which allows conventional Mecanum wheel movement. The four wheel groups are placed at the four corners of the frame, and the Mecanum wheels are arranged in an O-shaped pattern, so that the four wheels roll in the same direction, allowing the platform to move forward / reverse. When turning is required, the four wheels can rotate in different directions according to the parameters required for the turning, and the Mecanum wheels can be used to travel in curves in different directions. When the mobile platform is traversing obstacles or wading water, that is, when it needs to climb over obstacles, climb stairs and water areas, the deformation motor drives the worm to drive the deformation transmission worm wheel to rotate a certain angle, driving the deformation hollow shaft to rotate relative to the solid shaft, thereby driving the central deformation gear to engage with the three deformation half gears to rotate, forming a state of open swing arms; the deformation half gears are symmetrical and can also be unfolded in the reverse direction, so that the mobile platform can be unfolded in the reverse direction to climb stairs; at the same time, the Mecanum wheel roller changes direction to 0°, that is, the Mecanum wheel roller axis is parallel to the solid shaft, which is convenient for traversing obstacles and adhering to and paddling in water.