A two-stage optimization framework for a five-bar monoped achieves 42% greater jump distance and 15.8% lower mechanical energy consumption in simulation by co-optimizing design, actuators, and control.
Design principles for a family of direct-drive legged robots
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A dynamics-aware proprioceptive estimator recovers granular stiffness parameters consistently across hopping speeds by decomposing forces into inertia, gravity, and acceleration-dependent added-mass effects from grain entrainment.
A morphing five-bar linkage leg lets robots adapt between height-advantaged walking and force-advantaged rescue tasks.
citing papers explorer
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A Co-Design Framework for High-Performance Jumping of a Five-Bar Monoped with Actuator Optimization
A two-stage optimization framework for a five-bar monoped achieves 42% greater jump distance and 15.8% lower mechanical energy consumption in simulation by co-optimizing design, actuators, and control.
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From Impact to Insight: Dynamics-Aware Proprioceptive Terrain Sensing on Granular Media
A dynamics-aware proprioceptive estimator recovers granular stiffness parameters consistently across hopping speeds by decomposing forces into inertia, gravity, and acceleration-dependent added-mass effects from grain entrainment.
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Dynamically Extensible and Retractable Robotic Leg Linkages for Multi-task Execution in Search and Rescue Scenarios
A morphing five-bar linkage leg lets robots adapt between height-advantaged walking and force-advantaged rescue tasks.