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Transport and Delivery of Objects with a Soft Everting Robot

Ethan DeVries, Jack Ferlazzo, Mustafa Ugur, Laura H. Blumenschein

TL;DR

This work addresses delivering large or heavy payloads using soft everting robots by integrating theoretical models of growth, securing, and buckling with extensive experiments. It introduces an internally accessible tail channel that enables in-situ payload insertion and delivery, guided by swallowing-gripper–style securing physics. The combined theory and experiments show payloads up to about 1.5 kg can be transported through slopes, tight apertures, and unsupported gaps, with performance remaining robust under clutter and moderate control limits. The findings offer a pathway to deploy payloads in hazardous or constrained environments and establish design rules for mission planning and payload packaging in soft robotics applications.

Abstract

Soft everting robots present significant advantages over traditional rigid robots, including enhanced dexterity, improved environmental interaction, and safe navigation in unpredictable environments. While soft everting robots have been widely demonstrated for exploration type tasks, their potential to move and deploy payloads in such tasks has been less investigated, with previous work focusing on sensors and tools for the robot. Leveraging the navigation capabilities, and deployed body, of the soft everting robot to deliver payloads in hazardous areas, e.g. carrying a water bottle to a person stuck under debris, would represent a significant capability in many applications. In this work, we present an analysis of how soft everting robots can be used to deploy larger, heavier payloads through the inside of the robot. We analyze both what objects can be deployed and what terrain features they can be carried through. Building on existing models, we present methods to quantify the effects of payloads on robot growth and self-support, and develop a model to predict payload slip. We then experimentally quantify payload transport using soft everting robot with a variety of payload shapes, sizes, and weights and though a series of tasks: steering, vertical transport, movement through holes, and movement across gaps. Overall, the results show that we can transport payloads in a variety of shapes and up to 1.5kg in weight and that we can move through circular apertures with as little as 0.01cm clearance around payloads, carry out discrete turns up to 135 degrees, and move across unsupported gaps of 1.15m in length.

Transport and Delivery of Objects with a Soft Everting Robot

TL;DR

This work addresses delivering large or heavy payloads using soft everting robots by integrating theoretical models of growth, securing, and buckling with extensive experiments. It introduces an internally accessible tail channel that enables in-situ payload insertion and delivery, guided by swallowing-gripper–style securing physics. The combined theory and experiments show payloads up to about 1.5 kg can be transported through slopes, tight apertures, and unsupported gaps, with performance remaining robust under clutter and moderate control limits. The findings offer a pathway to deploy payloads in hazardous or constrained environments and establish design rules for mission planning and payload packaging in soft robotics applications.

Abstract

Soft everting robots present significant advantages over traditional rigid robots, including enhanced dexterity, improved environmental interaction, and safe navigation in unpredictable environments. While soft everting robots have been widely demonstrated for exploration type tasks, their potential to move and deploy payloads in such tasks has been less investigated, with previous work focusing on sensors and tools for the robot. Leveraging the navigation capabilities, and deployed body, of the soft everting robot to deliver payloads in hazardous areas, e.g. carrying a water bottle to a person stuck under debris, would represent a significant capability in many applications. In this work, we present an analysis of how soft everting robots can be used to deploy larger, heavier payloads through the inside of the robot. We analyze both what objects can be deployed and what terrain features they can be carried through. Building on existing models, we present methods to quantify the effects of payloads on robot growth and self-support, and develop a model to predict payload slip. We then experimentally quantify payload transport using soft everting robot with a variety of payload shapes, sizes, and weights and though a series of tasks: steering, vertical transport, movement through holes, and movement across gaps. Overall, the results show that we can transport payloads in a variety of shapes and up to 1.5kg in weight and that we can move through circular apertures with as little as 0.01cm clearance around payloads, carry out discrete turns up to 135 degrees, and move across unsupported gaps of 1.15m in length.

Paper Structure

This paper contains 20 sections, 8 equations, 11 figures.

Figures (11)

  • Figure 1: Soft everting robot carrying an object up a $45$-degree slope.
  • Figure 2: Payload-capable soft everting robot. A) Labels for the key features and components of the system. B) A free-body diagram of the forces acting on the payload within the pressurized inner pressure zone. C) Illustration of the system with the internal working channel pressurized to $P_C$ (orange) and the surrounding robot pressurized to $P_R$ (blue). Shown are the forces acting during growth while carrying an internal payload.
  • Figure 3: Behavior zones during slope climbing for a 4.35cm PETG cube payload on a 60° incline (shown by inset). A) shows the base case with no channel pressure; orange indicates $P_R$ is too low for growth to occur, green - growth with secure payload, purple, payload slip, orange–green stripes, the servo torque limit, and red, burst pressure. B–E) show effects of B) increasing $P_C$, C) increasing$\mu$, D) decreasing $D_{robot}$, or E) decreasing $\theta$.
  • Figure 4: Behavior zones during payload transport through a $90^\circ$ bend around an obstacle(shown by inset). A mix of robot pressure and servo torque is needed to achieve successful movement Values are based on a 6cm PETG sphere at a constant 1kPa channel pressure. Orange indicates no growth, green successful growth around the bend, and purple payload slip from contact with the obstacle.
  • Figure 5: Payload delivery performance and accuracy metrics. A) Uncluttered environment. B) Delivery results with MRE = 3.52cm, RSD = 3.61cm from the uncluttered environment. C) Cluttered environment. D) Delivery results with MRE = 9.13cm, RSD = 7.81cm from the cluttered environment.
  • ...and 6 more figures