Formation control of unmanned rotorcraft systems with state constraints and inter-agent collision avoidance

We present in this paper a novel framework and distributed control laws for the formation of multiple unmanned rotorcraft systems,be it single-rotor helicopters or multi-copters,with physical constraints and with inter-agent collision avoidance,in cluttered environments.The proposed technique is composed of an analytical distributed consensus control solution in the free space and an optimization based motion planning algorithm for inter-agent and obstacle collision avoidance.More specifically,we design a distributed consensus control law to tackle a series of state constraints that include but not limited to the physical limitations of velocity,acceleration and jerk,and an optimization-based motion planning technique is utilized to generate numerical solutions when the consensus control fails to provide a collision-free trajectory.Besides,a sufficiency condition is given to guarantee the stability of the switching process between the consensus control and motion planning.Finally,both simulation and real flight experiments successfully demonstrate the effectiveness of the proposed technique.

A robust online path planning approach in cluttered environments for micro rotorcraft drones

We present in this paper a robust online path planning method, which allows a micro rotorcraff drone to fly safely in GPS-denied and obstacle-strewn environments with limited onboard computational power. The approach is based on an effi- ciently managed grid map and a closed-form solution to the two point boundary value problem （TPBVP）. The grid map assists trajectory evaluation whereas the solution to the TPBVP generates smooth trajectories. Finally, a top-level trajectory switching algorithm is utilized to minimize the computational cost. Advantages of the proposed approach include its conservation of com- putational resource, robustness of trajectory generation and agility of reaction to unknown environment. The result has been realized on actual drones platforms and successfully demonstrated in real flight tests. The video of flight tests can be found at： http：//uav.ece.nus.edu.sg/robust-online-path-planning-Lai2015.html.

Decentralized MPC-Based Trajectory Generation for Multiple Quadrotors in Cluttered Environments

Challenges in motion planning for multiple quadrotors in complex environments lie in overall°ight e±ciency and the avoidance of obstacles,deadlock,and collisions among themselves.In this paper,we present a gradient-free trajectory generation method for multiple quadrotors in dynamic obstacle-dense environments with the consideration of time consumption.A model predictive control(MPC)-based approach for each quadrotor is proposed to achieve distributed and asynchronous cooperative motion planning.First,the motion primitives of each quadrotor are formulated as the boundary state constrained primitives(BSCPs)which are constructed with jerk limited trajectory(JLT)generation method,a boundary value problem(BVP)solver,to obtain time-optimal trajectories.They are then approximated with a neural network(NN),pre-trained using this solver to reduce the computational burden.The NN is used for fast evaluation with the guidance of a navigation function during optimization to guarantee°ight safety without deadlock.Finally,the reference trajectories are generated using the same BVP solver.Our simulation and experimental results demonstrate the superior performance of the proposed method.

Axis-coupled trajectory generation for chains of integrators through smoothing splines

Integrator based model is used to describe a wide range of systems in robotics. In this paper, we present an axis-coupled trajectory generation algorithm for chains of integrators with an arbitrary order. Special notice has been given to problems with pre-existing nominal plans, which are common in robotic applications. It also handles various type of constraints that can be satisfied on an entire time interval, including non-convex ones which can be transformed into a series of convex constraints through time segmentation. The proposed approach results in a linearly constrained quadratic programming problem, which can be solved effectively with off-the-shelf solvers. A closed-form solution is achievable with only the boundary constraints considered. Finally, the proposed method is tested in real experiments using quadrotors which represent high-order integrator systems.