Improving Collision Avoidance Behavior of a Target-Searching Algorithm for Kilobots

Collision avoidance in the area of swarm robotics is very important. The lacking ability of such collision avoidance is mentioned as one important reason for the sparse distribution of the small test robots named Kilobots. In this research paper, two new algorithms providing a collision avoidance strategy are presented and compared with previous research results. The first algorithm uses randomness to decide which one of several approaching Kilobots are stopped for a defined time before starting to move again. The second algorithm tries   to determine the assumed position of approaching Kilobots based on its radio signal strength and then to move away in the opposite direction by rotation. The results, especially of the second algorithm, are promising as the number of collisions can be significantly reduced

Dynamic Modeling and Analysis of Impact-resilient MAVs Undergoing High-speed and Large-angle Collisions with the Environment

Micro Aerial Vehicles (MAVs) often face a high risk of collision during autonomous flight, particularly in cluttered and unstructured environments. To mitigate the collision impact on sensitive onboard devices, resilient MAVs with mechanical protective cages and reinforced frames are commonly used. However, compliant and impact-resilient MAVs offer a promising alternative by reducing the potential damage caused by impacts. In this study, we present novel findings on the impact-resilient capabilities of MAVs equipped with passive springs in their compliant arms. We analyze the effect of compliance through dynamic modeling and demonstrate that the inclusion of passive springs enhances impact resilience. The impact resilience is extensively tested to stabilize the MAV following wall collisions under high-speed and large-angle conditions. Additionally, we provide comprehensive comparisons with rigid MAVs to better determine the tradeoffs in flight by embedding compliance onto the robot's frame.Comment: To appear in IROS 2023. Supplementary video https://youtu.be/b0xU2CzQWR

When Being Soft Makes You Tough: A Collision Resilient Quadcopter Inspired by Arthropod Exoskeletons

Flying robots are usually rather delicate, and require protective enclosures when facing the risk of collision. High complexity and reduced payload are recurrent problems with collision-tolerant flying robots. Inspired by arthropods' exoskeletons, we design a simple, easily manufactured, semi-rigid structure with flexible joints that can withstand high-velocity impacts. With an exoskeleton, the protective shell becomes part of the main robot structure, thereby minimizing its loss in payload capacity. Our design is simple to build and customize using cheap components and consumer-grade 3D printers. Our results show we can build a sub-250g, autonomous quadcopter with visual navigation that can survive multiple collisions at speeds up to 7m/s that is also suitable for automated battery swapping, and with enough computing power to run deep neural network models. This structure makes for an ideal platform for high-risk activities (such as flying in a cluttered environment or reinforcement learning training) without damage to the hardware or the environment

Stigmergy-based, Dual-Layer Coverage of Unknown Indoor Regions

We present algorithms for uniformly covering an unknown indoor region with a swarm of simple, anonymous and autonomous mobile agents. The exploration of such regions is made difficult by the lack of a common global reference frame, severe degradation of radio-frequency communication, and numerous ground obstacles. We propose addressing these challenges by using airborne agents, such as Micro Air Vehicles, in dual capacity, both as mobile explorers and (once they land) as beacons that help other agents navigate the region. The algorithms we propose are designed for a swarm of simple, identical, ant-like agents with local sensing capabilities. The agents enter the region, which is discretized as a graph, over time from one or more entry points and are tasked with occupying all of its vertices. Unlike many works in this area, we consider the requirement of informing an outside operator with limited information that the coverage mission is complete. Even with this additional requirement we show, both through simulations and mathematical proofs, that the dual role concept results in linear-time termination, while also besting many well-known algorithms in the literature in terms of energy use

Rotorigami: A rotary origami protective system for robotic rotorcraft

Applications of aerial robots are progressively expanding into complex urban and natural environments. Despite remarkable advancements in the field, robotic rotorcraft is still drastically limited by the environment in which they operate. Obstacle detection and avoidance systems have functionality limitations and substantially add to the computational complexity of the onboard equipment of flying vehicles. Furthermore, they often cannot identify difficult-to-detect obstacles such as windows and wires. Robustness to physical contact with the environment is essential to mitigate these limitations and continue mission completion. However, many current mechanical impact protection concepts are either not sufficiently effective or too heavy and cumbersome, severely limiting the flight time and the capability of flying in constrained and narrow spaces. Therefore, novel impact protection systems are needed to enable flying robots to navigate in confined or heavily cluttered environments easily, safely, and efficiently while minimizing the performance penalty caused by the protection method. Here, we report the development of a protection system for robotic rotorcraft consisting of a free-to-spin circular protector that is able to decouple impact yawing moments from the vehicle, combined with a cyclic origami impact cushion capable of reducing the peak impact force experienced by the vehicle. Experimental results using a sensor-equipped miniature quadrotor demonstrated the impact resilience effectiveness of the Rotary Origami Protective System (Rotorigami) for a variety of collision scenarios. We anticipate this work to be a starting point for the exploitation of origami structures in the passive or active impact protection of robotic vehicles

Exploration and Coverage with Swarms of Settling Agents

We consider several algorithms for exploring and filling an unknown, connected region, by simple, airborne agents. The agents are assumed to be identical, autonomous, anonymous and to have a finite amount of memory. The region is modeled as a connected sub-set of a regular grid composed of square cells. The algorithms described herein are suited for Micro Air Vehicles (MAV) since these air vehicles enable unobstructed views of the ground below and can move freely in space at various heights. The agents explore the region by applying various action-rules based on locally acquired information Some of them may settle in unoccupied cells as the exploration progresses. Settled agents become virtual pheromones for the exploration and coverage process, beacons that subsequently aid the remaining, and still exploring, mobile agents. We introduce a backward propagating information diffusion process as a way to implement a deterministic indicator of process termination and guide the mobile agents. For the proposed algorithms, complete covering of the graph in finite time is guaranteed when the size of the region is fixed. Bounds on the coverage times are also derived. Extensive simulation results exhibit good agreement with the theoretical predictions

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS