Continuum Deformation of a Multiple Quadcopter Payload Delivery Team without Inter-Agent Communication

This paper proposes continuum deformation as a strategy for controlling the collective motion of a multiple quadcopter system (MQS) carrying a common payload. Continuum deformation allows expansion and contraction of inter-agent distances in a 2D motion plane to follow desired motions of three team leaders. The remaining quadcopter followers establish the desired continuum deformation only by knowing leaders positions at desired sample time waypoints without the need for inter-agent communication over the intermediate intervals. Each quadcopter applies a linear-quadratic-Gaussian (LQG) controller to track the desired trajectory given by the continuum deformation in the presence of disturbance and measurement noise. Results of simulated cooperative aerial payload transport in the presence of uncertainty illustrate the application of continuum deformation for coordinated transport through a narrow channel

Education in the Crosscutting Sciences of Aerospace and Computing

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140664/1/1.i010193.pd

Qualitative Failure Analysis for a Small Quadrotor Unmanned Aircraft System

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106490/1/AIAA2013-4761.pd

An Evaluation of Flight Safety Assessment and Management to avoid Loss of Control during Takeoff

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140413/1/6.2014-0785.pd

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140667/1/1.i010350.pd

Flight Safety Assessment and Management during Takeoff

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106492/1/AIAA2013-4805.pd

Cyber–Physical Optimization for Unmanned Aircraft Systems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140662/1/1.i010105.pd

Optimization and Control of Cyber-Physical Vehicle Systems

A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined