Daniel Mellinger

Minimum snap trajectory generation and control for quadrotors

We address the controller design and the trajectory generation for a quadrotor maneuvering in three dimensions in a tightly constrained setting typical of indoor environments. In such settings, it is necessary to allow for significant excursions of the attitude from the hover state and small angle approximations cannot be justified for the roll and pitch. We develop an algorithm that enables the real-time generation of optimal trajectories through a sequence of 3-D positions and yaw angles, while ensuring safe passage through specified corridors and satisfying constraints on velocities, accelerations and inputs. A nonlinear controller ensures the faithful tracking of these trajectories. Experimental results illustrate the application of the method to fast motion (5–10 body lengths/second) in three-dimensional slalom courses.

Trajectory generation and control for precise aggressive maneuvers with quadrotors

We study the problem of designing dynamically feasible trajectories and controllers that drive a quadrotor to a desired state in state space. We focus on the development of a family of trajectories defined as a sequence of segments, each with a controller parameterized by a goal state or region in state space. Each controller is developed from the dynamic model of the robot and then iteratively refined through successive experimental trials in an automated fashion to account for errors in the dynamic model and noise in the actuators and sensors. We show that this approach permits the development of trajectories and controllers enabling such aggressive maneuvers as flying through narrow, vertical gaps and perching on inverted surfaces with high precision and repeatability.

Cooperative Grasping and Transport Using Multiple Quadrotors

In this paper, we consider the problem of controlling multiple quadrotor robots that cooperatively grasp and transport a payload in three dimensions.We model the quadrotors both individually and as a group rigidly attached to a payload. We propose individual robot control laws defined with respect to the payload that stabilize the payload along three-dimensional trajectories. We detail the design of a gripping mechanism attached to each quadrotor that permits autonomous grasping of the payload. An experimental study with teams of quadrotors cooperatively grasping, stabilizing, and transporting payloads along desired three-dimensional trajectories is presented with performance analysis over many trials for different payload configurations.

Design, modeling, estimation and control for aerial grasping and manipulation

This paper addresses mechanics, design, estimation and control for aerial grasping. We present the design of several light-weight, low-complexity grippers that allow quadrotors to grasp and perch on branches or beams and pick up and transport payloads. We then show how the robot can use rigid body dynamic models and sensing to verify a grasp, to estimate the the inertial parameters of the grasped object, and to adapt the controller and improve performance during flight. We present experimental results with different grippers and different payloads and show the robots ability to estimate the mass, the location of the center of mass and the moments of inertia to improve tracking performance.

Construction of Cubic Structures with Quadrotor Teams.

We propose and investigate a system in which teams of quadrotor helicopters assemble 2.5-D structures from simple structural nodes and members equipped with magnets. The structures, called Special Cubic Structures (SCS), are a class of 2.5-D truss-like structures free of overhangs and holes. Grippers attached to the bottom of each quadrotor enable them to pick up, transport, and assemble the structural elements. The design of the nodes and members imposes constraints on assembly which are incorporated into the design of the algorithms used for assembly. We show that any SCS can be built using only the feasible assembly modes for individual structural elements and present simulation and experimental results with a team of quadrotors performing automated assembly. The paper includes a theoretical analysis of the SCS construction algorithm, the rationale for the design of the structural nodes, members and quadrotor gripper, a description of the quadrotor control methods for part pickup, transport and assembly, and an empirical analysis of system performance.

Mixed-integer quadratic program trajectory generation for heterogeneous quadrotor teams

We present an algorithm for the generation of optimal trajectories for teams of heterogeneous quadrotors in three-dimensional environments with obstacles. We formulate the problem using mixed-integer quadratic programs (MIQPs) where the integer constraints are used to enforce collision avoidance. The method allows for different sizes, capabilities, and varying dynamic effects between different quadrotors. Experimental results illustrate the method applied to teams of up to four quadrotors ranging from 65 to 962 grams and 21 to 67 cm in width following trajectories in three-dimensional environments with obstacles with accelerations approaching 1g.

Influence of Aerodynamics and Proximity Effects in Quadrotor Flight

The dynamic response and performance of a micro UAV is greatly influenced by its aerodynamics which in turn is affected by the interactions with features in the environment in close proximity. In the paper we address the modeling of quadrotor robots in different flight conditions that include relative wind velocity and proximity to the ground, the ceiling and other robots. We discuss the incorporation of these models into controllers and the use of a swarm of robots to map features in the environment from variations in the aerodynamics.

Recent advances in quadrotor capabilities

Over the past year, our capabilities for the quadrotor platform have expanded significantly. This video represents a summary of our developments.

Incremental micro-UAV motion replanning for exploring unknown environments

This paper describes an approach to motion generation for quadrotor micro-UAVs navigating cluttered and partially known environments. We pursue a graph search method that, despite the high dimensionality of the problem, the complex dynamics of the system and the continuously changing environment model is capable of generating dynamically feasible motions in real-time. This is enabled by leveraging the differential flatness property of the system and by developing a structured search space based on state lattice motion primitives. We suggest a greedy algorithm to generate these primitives off-line automatically, given the robots motion model. The process samples the reachability of the system and reduces it to a set of representative, canonical motions that are compatible with the state lattice structure, which guarantees that any incremental replanning algorithm is able to produce smooth dynamically feasible motion plans while reusing previous computation between replans. Simulated and physical experimental results demonstrate real-time replanning due to the inevitable and frequent world model updates during micro-UAV motion in partially known environments.

Control and planning for vehicles with uncertainty in dynamics

This paper describes a motion planning algorithm that accounts for uncertainty in the dynamics of vehicles. This noise is a function of the type of controller employed on the vehicle and the characteristics of the terrain and can cause the robot to deviate from a planned trajectory and collide with obstacles. Our motion planning algorithm finds trajectories that balance the trade-off between conventional performance measures such as time and energy versus safety. The key is a characterization of the vehicles ability to follow planned paths, which allows the algorithm to explicitly calculate probabilities of successful traversal for different trajectory segments. We illustrate the method with a six-legged Rhex-like robot by experimentally characterizing different gaits (controllers) on different terrains and demonstrating the hexapod navigating a multi-terrain environment.