Ranging from autonomous flying cars, fixed wing and rotorcraft UAVs, there has been a tremendous interest in aerial robotics over the last decade. This thesis presents contributions to the state-of-art in cooperative payload transport with force synthesis and dynamic interaction using quadcopter UAVs. In this report, we consider multiple quadcopter aerial robots and develop decentralized force controller for them to manipulate a payload. We use quadcopters with a rigid link attached to it to collaboratively manipulate the payload. We develop a dynamic model of the payload for both point mass and rigid body cases. We model the contact force between the agents and the payload as a mass spring model. This assumption is valid when the vehicles are connected to the payload via elastic cables or when the payload is flexible or surrounded by elastic bumper materials. We also extend our aerial manipulation system to a multi-link arm attached to the quadcopter.We develop an adaptive decentralized control law for transporting a payload of unknown mass without explicit communication between the agents. Our controller ensures that all quadcopters and the payload asymptotically converges to a constant reference velocity. It also ensures that all of the forces applied to the payload converges to desired set-points. Desired thrusts and attitude angles are computed from the control algorithms and a low-level PD controller is implemented to track the desired commands for each quadcopter. The sum of the estimates of the unknown mass from all the agents converge to the true mass. We also employ a consensus algorithm based on connected graphs to ensure that each agent gets an equal share of the payload mass. Furthermore, we develop an orientation control algorithm that guarantees attitude stabilization of the payload. In particular, we develop time varying force set-points to enforce attitude regulation without any moment inputs from the quadcopters
