Faced with sand, gravel, and slopes, a robot with a rigid chassis might struggle to move, while the Raptor tracked chassis with its adaptive suspension handles such terrain with ease.
When we talk about robots, we often focus on their "brains"—the AI algorithms and perception systems—but easily overlook an equally critical part: their "legs" and "feet."
A well-designed chassis is the physical foundation that allows a robot to move from the lab into the complex real world. It not only determines where a robot can go but also directly affects the performance of its "brain": a bumpy platform interferes with sensor data, while a slipping chassis renders even the most precise control algorithm useless.
In robotic chassis design, terrain adaptability, motion stability, and rich extensibility form a solid performance triangle. These 3 aspects are interconnected and constrain each other. Designing an excellent tracked chassis is essentially about finding the optimal balance of this triangle.
Traditional rigid tracked chassis perform acceptably on flat surfaces, but once they encounter rough terrain, problems arise: wheels losing ground contact leading to loss of traction, chassis tilt causing distorted sensor data, and continuous shocks shortening the lifespan of electronic components.
The key to solving these problems lies in giving the chassis the ability to passively adapt to terrain. The core innovation of the Hiwonder Tracked Chassis is its patented High-Elasticity Torsion Spring Suspension System.
The design concept of this system is quite ingenious: when a road wheel is lifted by an obstacle, the connected swing arm forces the high-elasticity carbon steel torsion spring to deform. This physical process brings a triple advantage:
Passive Adaptation Without Power or Control: All road wheels maintain as much ground contact as possible, significantly increasing the contact area and stability. Efficient Energy Buffering: The torsion spring absorbs and gently releases impact energy, protecting sensors like LiDAR and depth cameras mounted on top. Continuous Traction Guarantee: Even if some wheels lose contact, the remaining wheels can still provide effective power, preventing slippage and power loss.
Having terrain adaptability is just the first step; precise and controllable motion is the key for robots to complete complex tasks. The Raptor chassis employs the classic differential drive structure but pushes the performance of this mature solution to new heights through a series of engineering optimizations.
The tracks on each side of the chassis are driven by independent high-precision encoded motors, forming a complete closed-loop control system. This means the controller can obtain the exact speed and rotation angle of the motors in real time and provide immediate compensation for abnormalities like slippage.
By finely controlling the speed difference between the two tracks, the robot can achieve flexible movements ranging from in-place rotation to turning with any radius.
Anti-slip design is another key consideration. The Raptor uses specially designed anti-slip nylon tracks. Their tooth profile effectively "bites" into various surfaces, providing greater adhesion.
The meshing between the drive sprocket and the track is precisely calculated to ensure efficient power transmission and reduce derailment risk. The design of the bearing-style road wheels minimizes running resistance, ensuring smooth power delivery to the ground.
A truly excellent chassis should not merely be a mobile platform but also a reliable carrier for sensors and intelligent systems. Advanced applications in robotics—whether SLAM mapping, dynamic obstacle avoidance, or coordinated robotic arm operations—place stringent demands on the chassis's stability and precision.
The Raptor's design fully considers these expansion needs. Its stable, shock-resistant characteristics provide a high-quality data acquisition foundation for LiDAR and depth cameras, which is a prerequisite for achieving high-precision environmental perception.
The accurate odometry information provided by the high-precision encoders and robust chassis allows the robot to significantly reduce accumulated error during SLAM mapping and navigation, enabling more reliable loop closure detection.
It is this exquisite balance between stability, precision, and adaptability that makes the Raptor chassis an ideal choice for many robotic projects. It serves as the core mobility platform for Hiwonder's own MentorPi T1 tracked robot and LanderPi mobile manipulator.
More importantly, it provides a reliable and powerful physical foundation for ROS2 learning, AI application development, and even cutting-edge embodied AI research.
Designing an exceptional tracked chassis is far more than simply assembling high-quality components. It is a complete engineering endeavor requiring systems thinking: the deep integration of ingenious mechanical structure, intelligent control algorithms, and the intended application scenarios.
The suspension system and differential control must work in concert to ensure both passability and precision. Hardware design must reserve sufficient expansion interfaces and load-bearing capacity to accommodate various potential future sensors and actuators.
More critically, the performance limits of the chassis directly determine the upper bound of what the upper-layer intelligent algorithms can achieve. A chassis that frequently slips or jolts renders even the most advanced environmental perception and path planning algorithms useless.
This deep synergy between hardware and software is the essence of modern robotic design.
Today, from educational labs to industrial sites, the Raptor chassis with its adaptive suspension is redefining the mobility of small robots. On the testing ground of a robotics startup in Shenzhen, a security robot equipped with this chassis easily traversed obstacles up to 8 cm high, while the point cloud data from its LiDAR remained stable.
This is not the victory of a single component, but proof of a systems-thinking approach. When the flexibility of suspension meets the precision of control, when mechanical reliability combines with intelligent expandability, robots truly gain the capability to explore a complex world.
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