In this paper we propose an algorithm to actively control the distance of a motor-propeller system (MPS) to a large obstacle using data from a single microphone. The method is based upon a broadband constructive/destructive interference pattern across the audible frequency band that is present when the MPS is near an obstacle. By taking the difference between the power spectrum in the obstacle-free case and the spectrum when recording near an obstacle, a broadband oscillation with respect to frequency is revealed. The frequency of this oscillation is linearly-related to the distance from the microphone to the wall. We present both static and dynamic experiments showcasing the ability of the proposed method to estimate the distance to a wall as well as actively control it.

This work describes our approach to controlling lighter-than-air agents using multimodal control via a wearable device. Tactile and gesture interfaces on a smart watch are used to control the motion and altitude of these semi-autonomous agents. The tactile interface consists of the touch screen and rotatable bezel. The gesture interface detects when the user puts his/her hand in the stop position. The touch interface controls the direction of the agents, the rotatable bezel controls the altitude set-point, and the gesture interface stops the agents. Our interactive demonstration will allow users to control a lighter-than-air (LTA) system via the multimodal wearable interface as described above.

Traditionally, localization systems for formation-keeping have required external references to a world frame, such as GPS or motion capture. Humans wishing to maintain formations with each other use visual line-of-sight, which is not possible in cluttered environments that may block their view. Our Local Positioning System (LPS) is based on ultra-wideband ranging devices and it enables teams of robots and humans to know their relative locations without line-of-sight. This demonstration shows live (real-time) local positioning between three agents (human and robot). The emphasis of this demonstration is showing the wearable interactive display that allows the human to see the local frame formation of the human and the robots.

This paper explores the feasibility and proposes a method on how to obtain high frequency real-time controllers operating in loop with physical robot hardware over a geographically adjacent and bounty hunting cloud server architecture. Having the cloud in the loop has many purposes including increasing computation, decreasing “on robot” power usage, reducing overall robot weight etc. Today when robots use the cloud in loop it is typically for sharing information, high level planning, and other non-real-time tasks. All of the balancing and stability algorithms stay onboard the robot. What if we could run high frequency real-time loops over the cloud? The better question is how would we do that? As with any real-time system latency is a big factor in the application and operation frequency. This paper shows that with a geographically adjacent and bounty hunting server approach it is feasible to obtain high frequency real-time control in loop with with a physical robot over the cloud. The feasibility of such a system running in-loop on humanoids and wheeled robots are explored and tested.

Supervision and teleoperation of high degree-of-freedom robots is a complex task due to environmental constraints such as obstacles and limited communication, as well as task specific requirements such as using more than one end-effector at the same time. In this work we present a supervision and teleoperation framework that allows an operator to see the surroundings of a robot in 3D, make necessary adjustments for a dual or single arm manipulation task, preview the task in simulation before execution, and finally execute the task on a real robot. The framework has been applied to the valve turning task of the DARPA Robotics Challenge on the PR2, Hubo2+, and DRCHubo robots.

Cloud robotics emphasizes harnessing the power of the Web for robotics. Modern mobile devices connect to the Web and are convenient user interfaces. We decided to explore what was possible at the intersection of robotics, the Web, and mobile devices by creating a mobile web interface for a humanoid robot. This paper describes our implementation of a monitoring interface for high degree of freedom (DOF) robots that works with both desktop and mobile devices. Using only standard web technologies, our application provides a rich 3D interface that displays the robot's pose, orientation, and sensor data, and can update at 30Hz. It is easy to use, because there is no software for the user to install; it runs using the device's mobile browser. The web interface can be deployed on a private or public cloud, and is designed to scale to support hundreds or thousands of viewers by utilizing cloud services. The system was successfully tested with two different robots and on multiple browsers and mobile devices.

In this paper, we report lessons learned through the design of a framework for teleoperating a humanoid robot to perform a manipulation task. We present a software framework for cooperative traded control that enables a team of operators to control a remote humanoid robot over an unreliable communications link. The framework produces statically-stable motion trajectories that are collision-free and respect end-effector pose constraints. After operator confirmation, these trajectories are sent over the data link for execution on the robot. Additionally, we have defined a clear operational procedure for the operators to manage the teleoperation task. We applied our system to the valve turning task in the DARPA Robotics Challenge (DRC). Our framework is able to perform reliably and is resilient to unreliable network conditions, as we demonstrate in a set of test runs performed remotely over the internet. We analyze our approach and discuss lessons learned which may be useful for others when designing such a system.

This work shows a method of creating trajectories to achieve end-effector velocity control for high degree of freedom position controlled, high-gain, robots. The focus of this work is throwing an object. It is shown that the full reachable area of the end-effector does not need to be known to achieve the desired velocity when a good collision model of the robot is available. The end-effector velocity (magnitude and direction) is specified as well as a duration of this velocity. A sparse map of reachable end-effector positions in free space and the corresponding poses in joint space is created using random sampling in joint space and forward kinematics. The desired trajectory in free space is placed within the sparse map with the first point of the trajectory being a known pose from the original sparse map. The Jacobian Transpose Controller method of inverse kinematics is then used to find the subsequent points in the trajectory. Each pose in the trajectory is checked against the collision model to guarantee no self-collisions. This method was tested on the 130 cm tall full size humanoid Jaemi Hubo and its virtual representation.

In pursuit of our long-term goal of developing an interactive humanoid musician, we are developing robust methods to determine musical beat locations from live acoustic sources. A variety of beat tracking systems have been previously developed, but for the most part they are optimized for direct audio input (no acoustic channel and no noise). The presence of an acoustic channel and noise typically degrades performance substantially. A robot's motors, in particular, create nonstationary noise that can be difficult for a beat detection system to accommodate, Using an algorithm previously developed by the authors, we explore techniques for reducing the effects of the acoustic channel and noise on the system, enabling a humanoid to robustly follow music under realistic conditions.