Various robot platforms have been developed for investigating new algorithms for swarm robotics. Morphogenetic engineering in robot swarms, however, proposes new requirements for platforms: precise motion control, physical interactions with the environment or neighbor robots, and functionalized shells. Few current platforms fulfill all the above characteristics. Here, we present Morphobot, a robot platform for morphogenetic engineering in swarm robotics. Its direct current coreless motors provide physical support and strong power, meanwhile, these needle-like motors also enhance the physical interactions among robots. Each Morphobot has a changeable shell. It is functionalized for programming local interactions, through physical contact or communication, among Morphobots. We characterized the mobility of Morphobot to test its capability of moving and physically interacting with its neighbors. To demonstrate its advantages in the morphogenesis of robot swarms, we designed two morphogenetic engineering experiments. The results revealed that swarms of Morphobots can form patterns via physical interactions and optical communications.

Motion modularity is the main method of motion control for higher animals. That means the complex movements of the muscles are made up of basic motion primitives, and the brain or central nervous system does not care about the specific details of the movement. However, the industrial robot control system does not adopt the technical roadmap of motion modularity, it generates complex trajectories by providing a large number of sampling points. This approach is equivalent to using the brain to directly guide the specific movement of the muscle and has to rely on a faster Fieldbus system to obtain complex motion trajectories. This work constructs a modularized industrial robot trajectory generation component based on Dynamic Movement Primitives (DMP) theory. With this component, the robot controller can generate complex trajectories without increasing the sampling points and can obtain good trajectory accuracy. Finally, the rationality of this system is proved by simulations and experiments.

Currently, the programming of multi robot control systems is difficult and requires high requirements for robot terminals. In response to the drawbacks of complex programming and easy interruption of message redundancy during communication in existing multi robot control systems, a multi robot control system based on MQTT is designed. MQTT is used as the communication protocol for multi robot communication, and a mobile robot experimental platform is built, this greatly reduces the redundancy of messages and the difficulty of manipulation in the control process of multiple robots. At the same time, the system has the function of action reproduction, which can record the actions of mobile robot terminals, reducing the difficulty of programming and debugging. Through experiments, the superiority of using MQTT protocol to control multiple robots has been verified. This system allows the robot to complete synchronous coordination work by only receiving commands from the upper computer and executing commands sent by the upper computer to the robot client, avoiding the need for the robot CPU to process a large amount of information and reducing the production cost of the robot. By controlling the robot’s actions through a human-computer interaction platform, errors can be corrected in a timely manner, and control methods can be adjusted without worrying about the robot’s actions making mistakes due to previous programs.

Aiming at the problem of insufficient endurance performance of flapping wing aircraft, a stable attitude control algorithm based on energy optimization and ESO (extended state observer) is designed, which effectively reduces the energy consumption in cruise phase. Firstly, the longitudinal dynamic model of flapping wing aircraft is established, and then the uncertain part of the system and various unknown external disturbances are taken as the total disturbance. ESO module is introduced to observe and track the total disturbance in real time. Therefore, the system is transformed into a series integral system through the total disturbance feedback, and then the energy optimal control law is designed on the base of the transformed system. The numerical simulation results show that, compared with the traditional PID control method, the designed energy optimal control method reduces the average energy consumption by 35.28%.

Flying insects have developed two distinct adaptive strategies to minimize wing damage during collisions. One strategy includes an elastic joint at the leading edge, which is evident in wasps and beetles, while another strategy features an adaptive and deformable leading edge, as seen in bumblebees and honeybees. Inspired by the latter, a novel approach has been developed for improving collision recovery in micro aerial vehicles (MAVs) by mimicking the principle of stiffness anisotropy present in the leading edges of these insects. This study introduces a passive, flexible, folding wing design with adaptive leading edges. The impact of these adaptive folding leading edges on the flight performance of flapping-wing MAVs was systematically evaluated. Variations in lift generation and obstacle-crossing capabilities between rigid wings and adaptive deformable wings were quantified. Additionally, the mechanical stiffness of the wings was assessed to validate their functional effectiveness. The proposed mechanism was incorporated into the wings of a dual-layer flapping-wing robot, which demonstrated successful flight recovery after collision. The experimental results indicate that a robot with a 30 cm wingspan can effectively traverse a gap of 16.2 cm during flight, thereby demonstrating its enhanced ability to overcome collision challenges. These findings underscore the potential of adaptive wing designs in enhancing the resilience and performance of MAVs in dynamic environments.

Compared with the tailless flapping wing micro air vehicle (FMAV), the tailed FMAV has a simpler structure and is easier to control. However, although biplane FMAVs with tails have been used for flight control in practice for a long time, a theoretical model of the tailed FMAV has not previously been established. In this paper, we report modeling of the longitudinal dynamics of a tailed biplane FMAV using the Newton‐Euler equations. In this study, the vehicle was trimmed and linearized near its hovering equilibrium, assuming small disturbances. Then the stability of the hovering FMAV was analyzed with a modal analysis method. A state feedback controller was synthesized to stabilize the disturbance. Finally, we investigated the flight control of the tailed biplane FMAV with different control signals. Our results show that the natural‐motion mode determines the oscillation divergence characteristics of the tailed FMAV, a mode that can be suppressed with the state feedback controller by real‐time modulation of the tail. The tail can also be used to achieve different flight modes with different control‐signal functions. The tailed FMAV cruises in a line when the tail is controlled with a step function and spirals in an elliptical trajectory in the longitudinal plane when the tail is controlled by a sinusoidal function. Our longitudinal‐ dynamics model provides an analytical basis for further dynamic analyses of the tailed FMAV, as well as the corresponding controller synthesis. Moreover, the proposed attitude stabilization and flight control schemes for the vehicle near hovering provide a basis for developing practical uses of the tailed FMAV.