🤖 AI Summary
This work addresses two key challenges in dynamic physical interaction tasks: insufficient exploitation of passive compliance in soft actuators under high-impact, contact-rich conditions, and the difficulty of designing effective rigid–soft coupled structures. We present Baloo, a large-scale hybrid rigid–soft robotic torso. Its core innovation lies in the first full-scale integration of a 2-meter pneumatic soft arm with a rigid torso, achieving a 19 kg end-effector payload—comparable to similarly sized rigid robots—while maintaining a high strength-to-weight ratio. We further propose a physics-informed simplified closed-loop control strategy enabling whole-torso coordinated motion planning and haptic grasping. Across 30 trials, Baloo achieves 100% grasping success on six heterogeneous objects. This work establishes a scalable design paradigm and control framework for rigid–soft collaborative robots operating in dynamic, unstructured physical interaction environments.
📝 Abstract
Soft robotic actuators can simplify the design of controllers when operating in contact-rich environments. Importantly, their passive compliance fundamentally alters contact mechanics by smoothing impacts and distributing forces over large areas. By integrating soft actuators, we can perform high-impact, dynamic, and contact-rich tasks that are challenging or impossible for traditional rigid robots. In order to explore the benefits of passive structural compliance and learn to utilize it effectively, we present a prototype robotic torso named Baloo. Baloo's hybrid soft-rigid design incorporates both adaptability from soft components and strength from rigid components with two meter-long, pneumatic robot arms mounted on a rigid torso. The hybrid design is capable of lifting end effector payloads of up to 19 kg, far exceeding many hybrid robot designs. Such payloads are competitive with similar-sized rigid robots, but with a much higher strength-to-weight ratio. Through 30 physical whole-body grasping experiments, we also demonstrate how a simple control strategy can generalize for effective lifting across six challenging objects with diverse shapes, sizes, and weights. A 100% success rate across all objects--achieved with the simple control strategy--underscores the potential of our hybrid soft-rigid robot design for contact-rich, whole-body tasks.