We give a system overview and initial experimental results for SIMbot (spherical induction motor based ballbot), a human-sized dynamically stable mobile robot with only two active moving parts. SIMbot is a qualitatively new kind of robot with the potential to drastically reduce mechanical complexity in human-sized mobile robots. SIMbot uses a novel spherical induction motor as its drive mechanism, which is mechanically simpler than other ballbot drive mechanisms. We demonstrate the feasibility of this innovation with experimental results for balancing, stationkeeping, short point-to-point motions, and recovery from initial lean angles.

Human-robot collaboration will increasingly take place in human social settings, including contexts where ethical and honest behavior is paramount. How might these robots affect human honesty? In this paper, we present first evidence of how a robot's presence affects people's ethical behavior in a controlled field study. We observed people passing by a food plate marked as “reserved”, comparing three conditions: no observer, a human observer, and a robot observer. We found that a human observer elicits less attention than a robot, but evokes more of a socially normative presence causing people to act honestly. Conversely, we found that a robot observer elicits more attention, engagement, and a monitoring presence. But even though people were suspicious that they were being monitored, they still behaved dishonestly in the robot observer condition.

This work presents a method for assisting people in getting out of chairs with a dynamically stable mobile robot. A user study is described in which force profiles and joint trajectories were recorded for a human-human sit-to-stand experiment. These data were used to develop an impedance-based controller designed to allow the ballbot to help people out of chairs. The control strategy is experimentally verified on the ballbot, a balancing mobile robot, exhibiting lean angles of over 15° and applying more than 120 N of assistive force. To our knowledge, this is the first mobile robot to assist people in standing.

The ballbot is a human sized, dynamically stable mobile robot that balances on a single, spherical wheel. The current framework for navigation and control makes the assumption that the robot is operating on a level surface without any center-of-mass offset; however, in practice, such a dynamically stable robot has to be able to successfully navigate sloped surfaces and with such offsets. This work develops the equations of motion for the ballbot system on a sloped surface with a center-of-mass offset. The equilibria of this system are analyzed, and a compensation strategy is formulated that allows the ballbot to operate in the presence of slopes and center-of-mass offsets. This work also develops estimation algorithms for slope and center-of-mass offset angles during station-keeping and trajectory following. Results for compensation and estimation are demonstrated experimentally.

This work presents a method to generate dynamically feasible trajectories for a balancing robot in the presence of obstacles, both static and moving. Intended for use on a ballbot, these trajectories respect the dynamics of the robot, and can be generated in milliseconds. Trajectories were experimentally verified on the ballbot in unstructured indoor environments at speeds up to .7 m/s and distances of up to 25 m. The method presented provides a tractable solution for indoor ballbot navigation, enabling safe movement through unstructured environments.

This work presents a method to find analytic and feasible trajectories for underactuated, balancing robots. The target application is fast computation of achievable trajectories for the ballbot, a dynamically stable mobile robot which balances on a single spherical wheel. To this end, assumptions are made to form the system as differentially flat, and a method of deriving feasible trajectories is shown. These trajectories are tracked on the real robot, demonstrating both point to point motions and recovery from nonzero initial conditions.

This video features advanced control capabilities for a quadrotor helicopter. We use an Ascending Technologies Hummingbird quadrotor [1] in conjunction with a Vicon [2] motion capture system in a flight arena [3] . The video shows a single quadrotor flying through windows with only three inches of clearance on any side of the platform and perching on vertical, declined, and inclined walls. Robustness to failed perching is demonstrated when it recovers to a stable hover from a failed perching attempt. Next, the video shows control along optimal trajectories through desired waypoints which includes flying through static and thrown hoops. Seen next is a gripper designed for the quadrotor to pickup objects and perch on horizontal surfaces. Finally, multiple quadrotors are shown cooperatively manipulating payloads to which they are rigidly attached.

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 robot's ability to estimate the mass, the location of the center of mass and the moments of inertia to improve tracking performance.