From biomimicry to robotic co-creation: rethinking the boundaries between nature and technology.

This paper is an invitation to an interdisciplinary dialogue on new possibilities for integrating robotics, design, and nature. I ask: how can new cross-movements between bio-inspired science and design be fostered? How might we envision the future possible intersection between technology and nature? First, I recall key aspects of classical bioinspired engineering and highlight the role of nature in the emergence of technology. Second, I introduce a new approach to bioinspired engineering. In this approach, robots play an active role in design and construction, learning from material properties to form new shapes and thus reshaping design paradigms. The distinctive elements of this approach depart from classical nature-inspired engineering and foster a symbiotic relationship between technology and nature. I conclude by reflecting on the intersections of nature, technology, and design, and envisioning new avenues for interdisciplinary dialogue that foster collaboration and innovation among diverse bio-inspired disciplines.

Platelet-Mimicking Nanosponges for Functional Reversal of Antiplatelet Agents.

BACKGROUND: During long-term antiplatelet agents (APAs) administration, patients with thrombotic diseases take a fairly high risk of life-threatening bleeding, especially when in need of urgent surgery. Rapid functional reversal of APAs remains an issue yet to be efficiently resolved by far due to the lack of any specific reversal agent in the clinic, which greatly restricts the use of APAs. METHODS: Flow cytometry analysis was first applied to assess the dose-dependent reversal activity of platelet-mimicking perfluorocarbon-based nanosponges (PLT-PFCs) toward ticagrelor. The tail bleeding time of mice treated with APAs followed by PLT-PFCs was recorded at different time points, along with corresponding pharmacokinetic analysis of ticagrelor and tirofiban. A hemorrhagic transformation model was established in experimental stroke mice with thrombolytic/antiplatelet therapy. Magnetic resonance imaging was subsequently applied to observe hemorrhage and thrombosis in vivo. Further evaluation of the spontaneous clot formation activity of PLT-PFCs was achieved by clot retraction assay in vitro. RESULTS: PLT-PFCs potently reversed the antiplatelet effect of APAs by competitively binding with APAs. PLT-PFCs showed high binding affinity comparable to fresh platelets in vitro with first-line APAs, ticagrelor and tirofiban, and efficiently reversed their function in both tail bleeding and postischemic-reperfusion models. Moreover, the deficiency of platelet intrinsic thrombotic activity diminished the risk of thrombogenesis. CONCLUSIONS: This study demonstrated the safety and effectiveness of platelet-mimicking nanosponges in ameliorating the bleeding risk of different APAs, which offers a promising strategy for the management of bleeding complications induced by antiplatelet therapy.

Programming material compliance and actuation: hybrid additive fabrication of biocomposite structures for large-scale self-shaping.

We present a hybrid approach to manufacturing a new class of large-scale self-shaping structures through a method of additive fabrication combining fused granular fabrication (FGF) and integrated hygroscopic wood actuators (HWAs). Wood materials naturally change shape with high forces in response to moisture stimuli. The strength and simplicity of this actuation make the material suitable for self-shaping architectural-scale components. However, the anisotropic composition of wood, which enables this inherent behavior, cannot be fully customized within existing stock. On the other hand, FGF allows for the design of large physical parts with multi-functional interior substructures as inspired by many biological materials. We propose to encode passively actuated movement into physical structures by integrating HWAs within 3D-printed meta-structures with functionally graded stiffnesses. By leveraging robotic manufacturing platforms, self-shaping biocomposite material systems can be upscaled with variable resolutions and at high volumes, resulting in large-scale structures capable of transforming from flat to curved simply through changes in relative humidity.

Integrating Non-spiking Interneurons in Spiking Neural Networks.

Researchers working with neural networks have historically focused on either non-spiking neurons tractable for running on computers or more biologically plausible spiking neurons typically requiring special hardware. However, in nature homogeneous networks of neurons do not exist. Instead, spiking and non-spiking neurons cooperate, each bringing a different set of advantages. A well-researched biological example of such a mixed network is a sensorimotor pathway, responsible for mapping sensory inputs to behavioral changes. This type of pathway is also well-researched in robotics where it is applied to achieve closed-loop operation of legged robots by adapting amplitude, frequency, and phase of the motor output. In this paper we investigate how spiking and non-spiking neurons can be combined to create a sensorimotor neuron pathway capable of shaping network output based on analog input. We propose sub-threshold operation of an existing spiking neuron model to create a non-spiking neuron able to interpret analog information and communicate with spiking neurons. The validity of this methodology is confirmed through a simulation of a closed-loop amplitude regulating network inspired by the internal feedback loops found in insects for posturing. Additionally, we show that non-spiking neurons can effectively manipulate post-synaptic spiking neurons in an event-based architecture. The ability to work with mixed networks provides an opportunity for researchers to investigate new network architectures for adaptive controllers, potentially improving locomotion strategies of legged robots.

Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems.

Internet of Things (IoT) and Cyber-Physical Systems (CPS) have profoundly influenced the way individuals and enterprises interact with the world. Although attacks on IoT devices are becoming more commonplace, security metrics often focus on software, network, and cloud security. For CPS systems employed in IoT applications, the implementation of hardware security is crucial. The identity of electronic circuits measured in terms of device parameters serves as a fingerprint. Estimating the parameters of this fingerprint assists the identification and prevention of Trojan attacks in a CPS. We demonstrate a bio-inspired approach for hardware Trojan detection using unsupervised learning methods. The bio-inspired principles of pattern identification use a Spiking Neural Network (SNN), and glial cells form the basis of this work. When hardware device parameters are in an acceptable range, the design produces a stable firing pattern. When unbalanced, the firing rate reduces to zero, indicating the presence of a Trojan. This network is tunable to accommodate natural variations in device parameters and to avoid false triggering of Trojan alerts. The tolerance is tuned using bio-inspired principles for various security requirements, such as forming high-alert systems for safety-critical missions. The Trojan detection circuit is resilient to a range of faults and attacks, both intentional and unintentional. Also, we devise a design-for-trust architecture by developing a bio-inspired device-locking mechanism. The proposed architecture is implemented on a Xilinx Artix-7 Field Programmable Gate Array (FPGA) device. Results demonstrate the suitability of the proposal for resource-constrained environments with minimal hardware and power dissipation profiles. The design is tested with a wide range of device parameters to demonstrate the effectiveness of Trojan detection. This work serves as a new approach to enable secure CPSs and to employ bio-inspired unsupervised machine intelligence.