Integrating Local Motion Planning and Robust Decentralized Fault-Tolerant Tracking Control for Search and Rescue Task of Hybrid UAVs and Biped Robots Team System

In this study, we integrate a local motion planning and robust H-8 decentralized observer-based feedforward reference tracking fault-tolerant control (FTC) of a hybrid UAVs and biped robots team system (URTS) for the purpose of search and rescue (S&R). A system architecture of performing S&R tasks for each agent in URTS is proposed to explain how to integrate reference trajectory planning and tracking control in URTS for S&R usage. In order to optimally allocate tasks to each agent in URTS, a task allocate problem is investigated. In order to optimally plan a path for each agent in URTS to reach these allocated task locations, a path planning problem is formulated. To deal with complex S&R terrain, we decompose the path planning problem into three steps, i.e., (i) global path planning, (ii) behavior decision and (iii) local motion planning. Through such decomposition, some roadmap-based path planning algorithms can be applied to the global path planning of agents in URTS. By the behavior decision, we can decide what behavior to follow the global path according to the terrain environment. Next, we focus on the local motion planning problem of flying behavior for UAV and walking behavior for robot, and then the tracking control problem for UAVs and robots in the hybrid team system. By a proposed novel feedforward linearization control scheme, the robust Hoo decentralized observer-based feedforward reference tracking FTC design is significantly simplified for each agent in URTS. A novel smoothing signal model of fault signal is embedded to achieve the active FTC through observer estimation. Then, the design of the robust H-8 decentralized observer-based feedforward reference tracking FTC strategy is transformed into a linear matrix inequality (LMI)-constrained optimization problem of each agent. With the help of MATLAB LMI Toolbox, the robust Hoo decentralized observer-based feedforward reference tracking FTC design problem of each UAV and robot in URTS is effectively solved. Finally, the simulation results are used to demonstrate the integration of local motion planning with the S&R tasks of hybrid URTS and to verify the effectiveness of the proposed robust H-8 decentralized observer-based feedforward reference tracking FTC method of hybrid URTS under the external disturbance and the actuator and sensor fault.

Automated summary

In this study, a local motion planning and robust H-8 decentralized observer-based feedforward reference tracking fault-tolerant control method is proposed for a hybrid UAVs and biped robots team system for search and rescue purposes. A system architecture is introduced to explain the integration of reference trajectory planning and tracking control in the team system. The path planning problem is decomposed into three steps to handle complex search and rescue terrain, and a novel feedforward linearization control scheme is used for the robust H-8 decentralized observer-based feedforward reference tracking FTC design.