Evasive Maneuvering for UAVs: An MPC Approach

Abstract

Abstract. Flying autonomously in a workspace populated by obstacles is one of the main goals when working with Unmanned Aerial Vehicles (UAV). To address this challenge, this paper presents a model predictive flight controller that drives the UAV through collision-free trajectories to reach a given pose or follow a waypoint path. The major advantage of this approach lies on the inclusion of threedimensional obstacle avoidance in the control layer by adding ellipsoidal constraints to the optimal control problem. The obstacles can be added, moved and resized online, providing a way to perform waypoint navigation without the need of motion planning. In addition, the delays of the system are cosidered in the prediction by an experimental first order with delay model of the system. Successful experiments in 3D path tracking and obstacle avoidance validates its effectiveness for sense-and-avoid and surveillance applications presenting the proper structure to extent its autonomy and applications.

Model Predictive Control for Aerial Collision Avoidance in Dynamic Environments

“…To provide safe navigation in cluttered dynamic scenarios we exploit active set algorithms to consider only the constraints that affect to our problem at each sample time. In this paper, we extend our previous work [15] by including the dynamics of ellipsoidal obstacles without additional cost. We use parametrized soft constraints to specify the sensitiveness of the avoidance maneuvers with the guarantee of finding a locally-optimal solution even in highly constrained scenarios as shown in Fig.…”

Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach

“…The values of the parameters k j and τ j presented in Sect. 5.2, have been calculated empirically, following the procedure described in [10], and are shown in Table 5.…”

“…To overcome the aforementioned difficulties, exploiting the high-performance of the embedded autopilots, the dynamics of multirotor aerial platforms can be represented employing simplified models that include the dynamic response of the autopilot, as in [10,53]. In these models, the control command given to the platform is the desired velocity of the aerial platform (both 1 DJI webpage: https://www.dji.com linear, and heading):…”

Towards trajectory planning from a given path for multirotor aerial robots trajectory tracking

“…We model our platform (mechanical part together with the autopilot with the velocity controller) following a similar procedure as described in [23]. We define the state of the aerial robot platform as:…”