This paper presents an algorithm for aerial vehicle trajectory generation based on the optimal Rapidly-exploring Random Tree (RRT*). The trajectory generation for the aerial vehicle is a complex path planning problem since the vehicle flies in a heterogeneous environment. The vehicle must also avoid some obstacles or inaccessible zones such as buildings, mountains and even radar detection zones depending on the mission. The RRT* algorithm is used as a basis to find near-optimal solutions for this problem. The shortest Dubins' path in heterogeneous environment is used to compute a distance and a trajectory between two vehicle states. Simulated results show the capability of the algorithm to find a feasible near-optimal trajectory in terms of path length that anticipates future flight conditions, such as the decrease in maneuverability in high altitude. The results also show the advantages over the numerical methods in avoiding obstacles.

This paper presents missile guidance as a complex robotic problem: a hybrid non-linear system moving in a heterogeneous environment. The proposed solution to this problem combines a sampling-based path planner, Dubins' curves and a locally-optimal guidance law. This algorithm aims to find feasible trajectories that anticipate future flight conditions, especially the loss of manoeuverability at high altitude. Simulated results demonstrate the substantial performance improvements over classical midcourse guidance laws and the benefits of using such methods, well-known in robotics, in the missile guidance field of research.

This paper presents a nonlinear controller for a vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) that exploits a measurement optical flow to enable hover and landing control on a moving platform, such as, for example, the deck of a sea-going vessel. The VTOL vehicle is assumed to be equipped with a minimum sensor suite [i.e., a camera and an inertial measurement unit (IMU)], manoeuvring over a textured flat target plane. Two different tasks are considered in this paper. The first concerns the stabilization of the vehicle relative to the moving platform that maintains a constant offset from a moving reference. The second concerns regulation of automatic vertical landing onto a moving platform. Rigorous analysis of system stability is provided, and simulations are presented. Experimental results are provided for a quadrotor UAV to demonstrate the performance of the proposed control strategy.

This paper presents a general approach for terrain following (including obstacle avoidance) of a vertical take-off and landing vehicle (VTOL) using multiple observation points. The VTOL vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera, IMU and barometric altimeter), manoeuvering over a textured rough terrain made of a concatenation of planar surfaces. Assuming that the forward velocity is separately regulated to a desired non-zero value, the proposed control approach ensures terrain following and guarantees the vehicle does not collide with obstacles during the task. The proposed control acquires an optical flow from multiple spatially separate observation points, typically obtained via multiple cameras or non collinear directions in a unique camera. The proposed control algorithm has been tested extensively in simulation and then implemented on a quadrotor UAV to demonstrate the performance of the closed loop system.

This paper presents a nonlinear controller for hovering flight and landing control on a moving platform for a Vertical Take-off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) by exploiting the measurement of the average optical flow. The VTOL vehicle is assumed to be equipped with a minimum sensor suite (a camera and an IMU), manoeuvring over a textured flat target plane. Two different tasks are considered in this paper: the first one concerns the stability of hovering flight and the second one concerns regulation of automatic vertical landing on a moving platform using the divergent optical flow as feedback information. Simulation and experimental results performed on a quad-rotor UAV demonstrate the performance of the proposed control strategy.

This paper presents a nonlinear controller for terrain following of a vertical take-off and landing vehicle (VTOL). The VTOL vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera and IMU) along with a measure of the forward speed from another sensor such as global positioning system, maneuvering over a textured terrain made of planar surfaces. Assuming that the forward velocity is separately set to a desired value, the proposed control approach ensures terrain following and guaranties the vehicle does not collide with the ground during the task. The proposed control acquires an optical flow from three spatially separate observation points, typically obtained via three cameras or three non collinear directions in a unique camera. The proposed control algorithm has been tested extensively in simulation and then implemented on a quadrotor UAV to demonstrate the performance of the closed loop system.

This paper presents a nonlinear controller for hovering flight and touchdown control for a vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) using inertial optical flow. The VTOL vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera and IMU), manoeuvring over a textured flat target plane. Two different tasks are considered in this paper: the first concerns the stability of hovering flight and the second one concerns regulation of automatic landing using the divergent optical flow as feedback information. Experimental results on a quad-rotor UAV demonstrate the performance of the proposed control strategy.