This paper presents an autonomous approach for landing a quadrotor on inclined surfaces up to 40 degrees using radar perception in a high particle environment, such as dust, rain, or fog. This system uses five radar sensors to determine the direction, angle, and smoothness of a slope through eigenvalue decomposition of a point cloud covariance matrix. The point cloud itself is generated using a FIFO queue with the radar sensors after their points are transformed to a common frame. Then, two asymmetric landing skids of different lengths actively conform to a slope in order to maintain level body attitude upon landing. For perception error tolerance, a study to understand the distance between the propeller and slope surface with respect to slope angles was developed. We evaluate the accuracy and consistency of radar sensors in accomplishing these tasks, to include a comparison of the results with a depth camera while in a high particle environment. Finally, the experimental result shows that the detected slope angle and direction were within 2.2 and 2.4 degrees of ground, and the proposed system is viable and robust for use in real-world applications.

In this work we present a Four-Wheeled Independent Drive and Steering (4WIDS) robot named AGRO and a method of controlling its orientation while airborne using wheel reaction torques. This is the first documented use of independently steerable wheels to both drive on the ground and achieve aerial attitude control when thrown. Inspired by a cat's self-righting reflex, this capability was developed to allow emergency response personnel to rapidly deploy AGRO by throwing it over walls and fences or through windows without the risk of it landing upside down. It also allows AGRO to drive off of ledges and ensure it lands on all four wheels. We have demonstrated a successful thrown deployment of AGRO.A novel parametrization and singularity analysis of 4WIDS kinematics reveals independent yaw authority with simultaneous adjustment of the ratio between roll and pitch authority. Simple PD controllers allow for stabilization of roll, pitch, and yaw. These controllers were tested in a simulation using derived dynamic equations of motion, then implemented on the AGRO prototype. An experiment comparing a controlled and non-controlled fall was conducted in which AGRO was dropped from a height of 0.85 m with an initial roll and pitch angle of 16 degrees and -23 degrees respectively. With the controller enabled, AGRO can use the reaction torque from its wheels to stabilize its orientation within 402 milliseconds.

In this paper, we present selected benchmark aerial manipulation tasks using an aerial vehicle endowed with multi-degree of freedom manipulators. The proposed tasks analyze environmental coupling and are broken into three general categories: momentary, loose, and strong coupling. A classical control structure is derived, tuned, and verified through experiments, conducted for benchmarking purposes to include pick-and-place, insertion, and valve-turning tasks. Although other nonlinear controllers may prove more effective, the classical control approach has been selected in order to analyze contact stability and provide benchmark results for future reference. An analysis of system stability is conducted and implemented into the controller. A vision-based high-level controller fuses motion tracking data in order to provide control of both the aircraft and the manipulators, allowing the system to become coupled to the environment and perform the required operation. We present recent results validating our framework using the proposed aircraft-arm system.

We propose a framework for valve turning using an aerial vehicle endowed with dual multi-degree of freedom manipulators. A tightly integrated control scheme between the aircraft and manipulators is mandated for tasks requiring aircraft to environmental coupling. Feature detection is well-established for both ground and aerial vehicles and facilitates valve detection and arm tracking. Force feedback upon contact with the environment provides compliant motions in the presence of position error and coupling with the valve. We present recent results validating the valve turning framework using the proposed aircraft-arm system during flight tests.

This paper presents a control scheme to achieve dynamic stability in an aerial vehicle with dual multi-degree of freedom manipulators. Arm movements assist with stability and recovery for ground robots, in particular humanoids and dynamically balancing vehicles. However, there is little work in aerial robotics where the manipulators themselves facilitate flight stability or the load mass is repositioned in flight for added control. We present recent results in arm motions that achieve increased flight stability without and with different load masses attached to the end-effectors. Our test flight results indicate that we can accurately model and control our aerial vehicle when both moving the manipulators and interacting with target objects.

Ongoing efforts toward mobile manipulation from an aerial vehicle are presented. Recent tests and results from a prototype rotorcraft have shown that our hybrid structure increases stability during flight and manipulation. Since UAVs require significant setup time, suitable testing locations, and have tendencies to crash, we developed an aerial manipulation test and evaluation environment that provides controllable and repeatable experiments. By using force feedback techniques, we have designed multiple, dexterous, redundant manipulators that can grasp objects such as tools and small objects. These manipulators are controlled in concert with an emulated aerial platform to provide hovering stability. The manipulator and aircraft flight control are tightly coupled to facilitate grasping without large perturbations in the end-effector.