From Problem to Solution: Bio-inspired 3D Printing for Bonding Soft and Rigid Materials via Underextrusions

Vertebrate animals benefit from a combination of rigidity for structural support and softness for adaptation. Similarly, integrating rigidity and softness can enhance the versatility of soft robotics. However, the challenges associated with creating durable bonding interfaces between soft and rigid materials have limited the development of hybrid robots. Existing solutions require specialized machinery, such as polyjet 3D printers, which are not commonly available. In response to these challenges, we have developed a 3D printing technique that can be used with almost all commercially available FDM printers. This technique leverages the common issue of underextrusion to create a strong bond between soft and rigid materials. Underextrusion generates a porous structure, similar to fibrous connective tissues, that provides a robust interface with the rigid part through layer fusion, while the porosity enables interlocking with the soft material. Our experiments demonstrated that this method outperforms conventional adhesives commonly used in soft robotics, achieving nearly 200\% of the bonding strength in both lap shear and peeling tests. Additionally, we investigated how different porosity levels affect bonding strength. We tested the technique under pressure scenarios critical to soft and hybrid robots and achieved three times more pressure than the current adhesion solution. Finally, we fabricated various hybrid robots using this technique to demonstrate the wide range of capabilities this approach and hybridity can bring to soft robotics. has context menu

A geometric approach towards inverse kinematics of soft extensible pneumatic actuators intended for trajectory tracking

Soft robots are interesting examples of hyper-redundancy in robotics, however, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials makes modeling of these robots more complicated. This study presents a geometric Inverse Kinematic (IK) model for trajectory tracking of multi-segment extensible soft robots, where, each segment of the soft actuator is geometrically approximated with multiple rigid links connected with rotary and prismatic joints. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions are obtained. Also, the redundancy of the robot is applied for second task applications, such as tip angle control. The model's performance is investigated through simulations, numerical benchmarks, and experimental validations and results show lower computational costs and higher accuracy compared to most existing methods. The method is easy to apply to multi segment soft robots, both in 2D and 3D. As a case study, a fully 3D-printed soft robot manipulator is tested using a control unit and the model predictions show good agreement with the experimental results.

A Bioinspired Stiffness Tunable Sucker for Passive Adaptation and Firm Attachment to Angular Substrates

The ability to adapt and conform to angular and uneven surfaces improves the suction cup's performance in grasping and manipulation. However, in most cases, the adaptation costs lack of required stiffness for manipulation after surface attachment; thus, the ideal scenario is to have compliance during adaptation and stiffness after attachment to the surface. Nevertheless, most stiffness modulation techniques in suction cups require additional actuation. This article presents a new stiffness tunable suction cup that adapts to steep angular surfaces. Using granular jamming as a vacuum driven stiffness modulation provides a sensorless for activating the mechanism. Thus, the design is composed of a conventional active suction pad connected to a granular stalk, emulating a hinge behavior that is compliant during adaptation and has high stiffness after attachment is ensured. During the experiment, the suction cup can adapt to angles up to 85 degrees with force lower than 0.5 N. We also investigated the effect of granular stalk's length on the adaptation and how this design performs compared to passive adaptation without stiffness modulation.