ATMO: An Aerially Transforming Morphobot for Dynamic Ground-Aerial Transition
🤖 AI Summary
Ground–aerial reconfigurable robots struggle to simultaneously achieve robust morphological transitions and high locomotion efficiency on rough terrain. Method: This paper introduces a novel near-ground aerial reconfiguration paradigm. We design ATMO, a morphology-reconfigurable robot that leverages ground effect for stable landing under actuator-saturated, over-actuated姿态 configurations—first of its kind. A ground-distance-adaptive, configuration-coupled model predictive controller (MPC) enables real-time closed-loop stabilization during dynamic reconfiguration. The approach integrates multi-modal mechanical design, aerodynamic characterization via wind-tunnel experiments, and deformation-state feedback. Results: Experiments demonstrate smooth, repeated transitions between aerial and ground modes, significantly enhancing terrain adaptability and reconfiguration robustness under actuator saturation—overcoming fundamental aerodynamic and actuation limitations inherent in conventional high-altitude reconfiguration strategies.
Application Category
📝 Abstract
Designing ground-aerial robots is challenging due to the increased actuation requirements which can lead to added weight and reduced locomotion efficiency. Morphobots mitigate this by combining actuators into multi-functional groups and leveraging ground transformation to achieve different locomotion modes. However, transforming on the ground requires dealing with the complexity of ground-vehicle interactions during morphing, limiting applicability on rough terrain. Mid-air transformation offers a solution to this issue but demands operating near or beyond actuator limits while managing complex aerodynamic forces. We address this problem by introducing the Aerially Transforming Morphobot (ATMO), a robot which transforms near the ground achieving smooth transition between aerial and ground modes. To achieve this, we leverage the near ground aerodynamics, uncovered by experimental load cell testing, and stabilize the system using a model-predictive controller that adapts to ground proximity and body shape. The system is validated through numerous experimental demonstrations. We find that ATMO can land smoothly at body postures past its actuator saturation limits by virtue of the uncovered ground-effect.
Problem
Research questions and friction points this paper is trying to address.
Addresses challenges in ground-aerial robot design
Overcomes ground-vehicle interaction complexity during morphing
Enables smooth transition between aerial and ground modes
Innovation
Methods, ideas, or system contributions that make the work stand out.
Aerially transforming robot for smooth mode transition
Utilizes near ground aerodynamics for stabilization
Model-predictive controller adapts to ground proximity
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