Although the off-road mobility characteristics of wheeled or tracked vehicles are generally recognized as being inferior to those of man and cursorial animals, the complexity of the joint-coordination control problem has thus far frustrated attempts to achieve improved vehicular terrain adaptability through the application of legged locomotion concepts. Nevertheless, the evident superiority of biological systems in this regard has motivated a number of theoretical studies over the past decade which have now reached a state of maturity sufficient to permit the construction of experimental computer-controlled adaptive walking machines. At least two such vehicles are known to have recently demonstrated legged locomotion over smooth hard-surfaced terrain. This paper is concerned with an extension of the present theory of limb coordination for such machines to the case in which the terrain includes regions not suitable for weight-bearing and which must consequently be avoided by the control computer in deciding when and where to successively place the feet of the vehicle. The paper includes a complete problem formalization, a heuristic algorithm for solution of the problem thus posed, and a preliminary evaluation of the proposed algorithm in terms of a computer simulation study.

Adaptive Locomition of a Multilegged Robot over Rough Terrain

International Conference on Robotics and Automation (ICRA)

Recent progress in and perspectives of underwater wireless optical communication

Distributed cooperative encirclement hunting guidance for multiple flight vehicles system

This article investigates the moving-target circular formation control problem for multiple nonholonomic vehicles under a directed graph. First, a novel moving-target enclosing control scheme is proposed by using the feedback linearization approach, in which the design procedure of the cooperative controller is more straightforward. Compared with the existing literature, the designed controller relaxes some existing constraints and the corresponding stability analysis is more concise. Second, based on the distance measurements, the observers, including sliding-mode observer and relative position observer, are designed to estimate the relative position so that the global position measurements are not required. Therefore, the observer-based controller becomes more suitable for practical application. Numerical simulations are conducted to illustrate the effectiveness of the proposed controllers.

Cooperative Moving-Target Enclosing Control for Multiple Nonholonomic Vehicles Using Feedback Linearization Approach

In this Letter, the broadband operation in wavelengths from 520 nm to 980 nm is demonstrated on silicon nitride nanophotonic phased arrays. The widest beam steering angle of 65° on a silicon nitride phased array is achieved. The optical radiation efficiency of the main grating lobe in a broad wavelength range is measured and analyzed theoretically. The optical spots radiated from the phased array chip are studied at different wavelengths of lasers. The nanophotonic phased array is excited by a supercontinuum laser source for a wide range of beam steering for the first time to the best of our knowledge. It paves the way to tune the wavelength from visible to near infrared range for silicon nitride nanophotonic phased arrays.

Broadband silicon nitride nanophotonic phased arrays for wide-angle beam steering.

This paper investigates the cooperative moving-target enclosing control problem of networked unicycle-type nonholonomic vehicles with constant linear velocities. The information of the target is only known to some of the vehicles, and the topology of the vehicle network is described by a directed graph. A dynamic control law is proposed to steer the vehicles, such that they can get close to orbiting around the target while the target is moving with a time-vary velocity. Besides, the constraint of bounded angular velocity for the vehicles can always be satisfied. The proposed control law is distributed in the sense that each vehicle only uses its own information and the information of its neighbors in the network. Finally, simulation results of an example validate the effectiveness of the proposed control law.

Cooperative Moving-Target Enclosing of Networked Vehicles With Constant Linear Velocities

Underwater wireless optical communication (UWOC) will play an important role in the underwater environment exploration and marine resource development due to its advantages of high data rate and good mobility. However, the significant signal power attenuation in the underwater channel limits the transmission distance of UWOC. Attenuation length (AL) is widely used as an indicator for evaluating the UWOC system's long-distance transmission capability. At present, Gbps UWOC is limited within 7AL. Using a SiPM based receiver can dramatically increase the AL that UWOC can support. In this paper, a novel UWOC receiver built from an off-the-shelf SiPM has been demonstrated. The finite pulse width and limited bandwidth of SiPM limit the SiPM based UWOC system's data rate. To boost the system's data rate, an optimum method to process the SiPM's signal has therefore been investigated. Based on these methods, the communication capabilities of the SiPM based UWOC have been investigated experimentally. Results show that the SiPM based receiver can support 11.6AL without turbulence and 9.28AL within weak turbulence (scintillation index = 0.0447) at 1 Gbps.

Over 10 attenuation length gigabits per second underwater wireless optical communication using a silicon photomultiplier (SiPM) based receiver.

In underwater optical wireless communication (UOWC) systems, using single photon avalanche photondiode (SPAD) as the detector can improve the transmission distance. However, the signal detection for SPAD-based systems is greatly challenged by the complex optical channel characteristics and SPAD nonlinear distortion. To address this issue, a novel deep learning aided signal detection scheme is proposed in this paper. By exploiting the physical mechanism and prior expert knowledge of the signal processing, a two-connected multilayer perception (MLP) network is integrated into the receiver. The first subnetwork is regarded as a channel compensation block while the second one works as a demodulator. With sophisticated numerical optical channel model and SPAD non-Poisson model, large amounts of training data are utilized to train the proposed model offline. Afterwards, the online data are recovered with the trained network. Simulation results verify that significant bit error ratio (BER) improvement can be achieved with the proposed scheme.

Deep Learning Aided Signal Detection for SPAD-Based Underwater Optical Wireless Communications

This paper investigates the cooperative target enclosing of multiple unicycle-type mobile robots subject to input disturbances. The objective is to make all robots orbit around a given stationary target, and maintain evenly spaced along a common circle. The network of the multirobot systems is set in a cyclic pursuit manner. A dynamic control law is developed for the cooperative target enclosing of the multirobot systems, while tackling the heterogeneous input disturbances generated by linear exogenous systems. The proposed control law requires each robot to use the relative displacement measurements with respect to the target and its neighbors. It is shown that global asymptotic stability of the closed-loop multirobot systems can be guaranteed in the presence of a large class of input disturbance signals. Finally, simulation results illustrate the effectiveness of our approach.

Aidong Zhang

Papers

Broadband silicon nitride nanophotonic phased arrays for wide-angle beam steering.

Cooperative Moving-Target Enclosing of Networked Vehicles With Constant Linear Velocities

Over 10 attenuation length gigabits per second underwater wireless optical communication using a silicon photomultiplier (SiPM) based receiver.

Deep Learning Aided Signal Detection for SPAD-Based Underwater Optical Wireless Communications

Cooperative Target Enclosing Control of Multiple Mobile Robots Subject to Input Disturbances