We present a real-time monocular simultaneous localization and mapping (SLAM) system with a new distributed structure for multi-UAV collaboration tasks. The system is different from other general SLAM systems in two aspects: First, it does not aim to build a global map, but to estimate the latest relative position between nearby vehicles; Second, there is no centralized structure in the proposed system, and each vehicle owns an individual metric map and an ego-motion estimator to obtain the relative position between its own map and the neighboring vehicles’. To realize the above characteristics in real time, we demonstrate an innovative feature description and matching algorithm to avoid catastrophic expansion of feature point matching workload due to the increased number of UAVs. Based on the hash and principal component analysis, the matching time complexity of this algorithm can be reduced from O (log N ) to O (1). To evaluate the performance, the algorithm is verified on the acknowledged multi-view stereo benchmark dataset, and excellent results are obtained. Finally, through the simulation and real flight experiments, this improved SLAM system with the proposed algorithm is validated.

Aquatic-aerial multimodal vehicle is a new concept aircraft that can freely shuttle between water and air. Some of the natural organisms provide the inspiration to realize this multi-locomotion. Most of current prototypes use rigid link mechanisms or hinges to morph the structure thus to adapt to the aquatic-aerial environment, which is commonly complicated and bulky. In this paper, we present a novel prototype with pneumatically-driven soft fins and arms that can fold and spread just like the flying squid. The fins and arms can augment the lift force during flying by spreading and reduce drag force during swimming by folding. The performance of the morphable structures was investigated in wind and water tunnel. The results explain the tradeoff strategies of multimodal-locomotion between water and air, and verify the feasibility of the novel aquatic-aerial vehicle with soft morphable structures.

This paper presents a biomimetic robotic fish that swims using thunniform kinematics for advanced underwater mobility. Propulsion and maneuvering of the robotic fish are achieved with a lunate caudal fin that undergoes combined translational and rotational motion. A parallel four-bar propulsive mechanism attached to the rear of the rigid torpedo-shaped body is used to deliver motor rotation to the caudal fin. Oscillatory control signals for the tail joints are generated with a CPG controller composed of two unidirectionally coupled Hopf oscillators. Coupling terms that allow direct specification of phase relation between oscillators are formulated. The maximum speed of the robotic fish can reach 2.0 m/s and excellent maneuverability has been exhibited. The outstanding swimming performances present exciting possibilities for real-world deployment of the robotic fish.

This paper presents a learning method to acquire fish-liking swimming with a CPG-based locomotor controller. The proposed method converts the related CPG parameters into dynamical systems that evolve as part of the CPG network dynamics. The teaching signals are derived from the kinematic model of carangiform swimming with trajectory approximation method. A novel coupling scheme for the CPG network, which are modeled as a chain of coupled Hopf oscillators is proposed to eliminate the influence of afferent signals on amplitude of the oscillator. The learning rules of intrinsic frequency, coupling weight and amplitude are formulated with phase space representation of the oscillators. The frequency, amplitudes and phase relations of the teaching signals can be encoded by the CPG network with the adaptation mechanisms. Numerical experiments are carried out to validate the effectiveness of the proposed learning rules.

This paper presents an underwater cooperative box-pushing scenario in which three autonomous robotic fish that sense, plan and act on their own move an elongated box from some initial location to a goal location. With the onboard monocular camera, the robotic fish can estimate the pose of the object in the swimming tank. Considering the complexity of the underwater environment and the limited capability of a single robotic fish, we address the task by decomposing it into three subtasks and assigning them to capable robotic fish. With one robotic fish observing the box at the goal location and two robotic fish pushing the left and right ends of the box, the box can be moved gradually towards the goal location. The subtask consists a series of behaviors, each designed to fulfill one step of the subtask. The robotic fish coordinate through explicit communications and distribute the subtasks with a market-based dynamic task allocation method. Task reallocation mechanism that permits robotic fish to auction its assigned task to capable ones is used to cope with unexpected changes in the environment and the limited sensing range of the robotic fish. Experiments are conducted to verify the feasibility of the proposed methods.

Hydrodynamic investigation of carangiform robotic fish has been carried out by using a novel experimental method. The laboratory robotic fish model which follows an exact replica of Saithe, is self-propelled on a servo towing system. The forward towing speed is determined by the fluid force acting upon the robotic fish, as the fish undulate its body in the water. The importance of the self-propelled method which allows for simultaneous measurement of internal and extern force and flow analysis of robotic fish has been demonstrated in the hydrodynamic experiment.

This paper describes the design of a biomimetic inspired fish swimming like UUV based on 2-D ocillating foil machanism which plays guiding role in biomimetic propulsion research field, the relation between vorticity control and motion control parameters for 2-D ocillating foil has been built, a fuzzy logic vorticity controller is designed to achieve straight line maneuverable swimming and thrust efficiency can be ensured at the same time. Experimental result of field test shows that an obiviously improved vehicle performance is obtained. Meanwhile, burst-and-coast manevering is found to be a more effective swimming mode for the vihicle while compared with steady swimming.

The reconfigurable tracked mobile robot was developed for all-terrain recon. Based on the unique characters of reconfigurable robot, modular mechanical and electrical structure and control method were all discussed. The tracked robot was composed of four basic locomotion modules, three joint rods and two rotational articulations. By the different configurations of all the modules, the mechanical reconfiguration of the tracked vehicle was realized. The master-slave control system was adopted. Based on the ARM real time embedded control system, the reconfiguration was realized when the mechanical structure of the robot was reconfigured. The tracked robot was validated that it has the excellent adaptable ability in complex terrain and has easy and simple reconfigurable performance when it executed recon in the building interior simulating the real task

To reduce the yawing, rolling and pitching of the fish robot and to improve the efficiency of tail fin propulsion, the strength environment of the tail fin thruster was analyzed, the fish robot's shape is optimized under a novel design principle, which was abbreviated as SPC (stability first, propulsion second, control third), of bionic fish robot, the result was analyzed by computer fluid dynamics simulation using the lift-drag ratio as the key parameter. The experiments of three fish robots of different scales were done. The biggest one, which was 2m in length, reached the maximal speed of 1.5m/s at the frequency of 1.6Hz. And the yawing of all three fish robots were below 5/spl deg/. The experiments have shown that owing to the improvement of the stabilization the velocity and propulsion efficiency were also improved, and the Strouhal number got into the best region of 0.2-0.3.