Energy-Efficient Trajectory Optimization for UAV-Based Hybrid FSO/RF Communications with Buffer Constraints

This paper focuses on an unmanned aerial vehicle (UAV) assisted hybrid free-space optical (FSO)/radio frequency (RF) communication system. Considering the rate imbalance between the FSO and RF links, a buffer is employed at the UAV. Initially, theoretical models of energy consumption and throughput are obtained for the hybrid system. Based on these models, the theoretical expression of the energy efficiency is derived. Then, a nonconvex trajectory optimization problem is formulated by maximizing the energy efficiency of the hybrid system under the buffer constraint, velocity constraint, acceleration constraint, start–end position constraint, and start–end velocity constraint. By using the sequential convex optimization and first-order Taylor approximation, the nonconvex problem is transformed into a convex one. An iterative algorithm is proposed to solve the problem. Numerical results verify the efficiency of the proposed algorithm and also show the effects of buffer size on a UAV’s trajectory.

Finite-time Tracking Control with Velocity Constraints for the Stochastic Rehabilitative Training Walker System Considering Different Rehabilitee Masses

This study discusses a finite-time tracking controller for a rehabilitative training walker that imposes velocity constraints. The walker was described using a stochastic model through which the rehabilitee mass can randomly change, and a velocity constraint method was proposed to control the velocity input to every omniwheel based on a model predictive algorithm. This approach is novel in that the velocity constraint information obtained from the kinematics model was used to design the tracking controller based on the stochastic dynamic model, thus successfully constraining the actual velocity of walker as per the stochastic system. The nonlinear tracking controller was built for the stochastic rehabilitative walker to make the system’s finite time stable. Also, simulation and experiment were performed, and results confirmed that the proposed tracking control method with velocity constraints is very effective, so it may enable various rehabilitees to train safely.

Stereo visual odometry with velocity constraint for ground vehicle applications

This paper proposes a novel method of error mitigation for stereo visual odometry (VO) applied in land vehicles. A non-holonomic constraint (NHC), which imposes physical constraint to the rightward velocity of a land vehicle, is implemented as an observation in an extended Kalman filter (EKF) to reduce the drift of stereo VO. The EKF state vector includes position errors in an Earth-centred, Earth-fixed (ECEF) frame, velocity errors in the camera frame, angular rate errors and attitude errors. All the related equations are described and presented in detail. In this approach, no additional sensors are used but NHC, namely velocity constraint in the right direction , is applied as an external measurement to improve the accuracy. Tests are conducted with the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) datasets. Results show that the relative horizontal positioning error improved from 0⋅63% to 0⋅22% on average with the application of the velocity constraints. The maximum and root mean square of the horizontal error with velocity constraints are both reduced to less than half of the error with stand-alone stereo VO.