A Soft-Bodied Aerial Robot for Collision Resilience and Contact-Reactive Perching.

Current aerial robots demonstrate limited interaction capabilities in unstructured environments when compared with their biological counterparts. Some examples include their inability to tolerate collisions and to successfully land or perch on objects of unknown shapes, sizes, and texture. Efforts to include compliance have introduced designs that incorporate external mechanical impact protection at the cost of reduced agility and flight time due to the added weight. In this work, we propose and develop a lightweight, inflatable, soft-bodied aerial robot (SoBAR) that can pneumatically vary its body stiffness to achieve intrinsic collision resilience. Unlike the conventional rigid aerial robots, SoBAR successfully demonstrates its ability to repeatedly endure and recover from collisions in various directions, not only limited to in-plane ones. Furthermore, we exploit its capabilities to demonstrate perching where the three-dimensional collision resilience helps in improving the perching success rates. We also augment SoBAR with a novel hybrid fabric-based bistable (HFB) grasper that can utilize impact energies to perform contact-reactive grasping through rapid shape conforming abilities. We exhaustively study and offer insights into the collision resilience, impact absorption, and manipulation capabilities of SoBAR with the HFB grasper. Finally, we compare the performance of conventional aerial robots with the SoBAR through collision characterizations, grasping identifications, and experimental validations of collision resilience and perching in various scenarios and on differently shaped objects.

Transient bio-inspired gliders with embodied humidity responsive actuators for environmental sensing.

Collecting temporal and spatial high-resolution environmental data can guide studies in environmental sciences to gain insights in ecological processes. The utilization of automated robotic systems to collect these types of data can maximize accuracy, resilience, and deployment rate. Furthermore, it reduces the risk to researchers deploying sensors in inaccessible environments and can significantly increase the cost-effectiveness of such studies. The introduction of transient robotic systems featuring embodied environmental sensors pushes towards building a digital ecology, while introducing only minimal disturbance to the environment. Transient robots made from fully biodegradable and non-fossil based materials, do not develop into hazardous e-waste at the end of their lifetime and can thus enable a broader adoption for environmental sensing in the real world. In this work, our approach towards the design of transient robots includes the integration of humidity-responsive materials in a glider, which is inspired by the Alsomitra macrocarpa seed. The design space of these gliders is explored and their behavior studied numerically, which allows us to make predictions on their flight characteristics. Results are validated against experiments, which show two different gliding behaviors, that can help improve the spread of the sensors. By tailoring the Cellulose-Gelatin composition of the humidity actuator, self-folding systems for selective rainwater exposure can be designed. The pH sensing layer, protected by the actuator, provides visual feedback on the pH of the rainwater. The presented methods can guide further concepts developing transient aerial robotic systems for sustainable, environmental monitoring.

Model-based contact detection and position control of a fabric soft robot in unknown environments.

Soft robots have shown great potential to enable safe interactions with unknown environments due to their inherent compliance and variable stiffness. However, without knowledge of potential contacts, a soft robot could exhibit rigid behaviors in a goal-reaching task and collide into obstacles. In this paper, we introduce a Sliding Mode Augmented by Reactive Transitioning (SMART) controller to detect the contact events, adjust the robot's desired trajectory, and reject estimated disturbances in a goal reaching task. We employ a sliding mode controller to track the desired trajectory with a nonlinear disturbance observer (NDOB) to estimate the lumped disturbance, and a switching algorithm to adjust the desired robot trajectories. The proposed controller is validated on a pneumatic-driven fabric soft robot whose dynamics is described by a new extended rigid-arm model to fit the actuator design. A stability analysis of the proposed controller is also presented. Experimental results show that, despite modeling uncertainties, the robot can detect obstacles, adjust the reference trajectories to maintain compliance, and recover to track the original desired path once the obstacle is removed. Without force sensors, the proposed model-based controller can adjust the robot's stiffness based on the estimated disturbance to achieve goal reaching and compliant interaction with unknown obstacles.