In this work, we present a control framework to effectively maneuver wheelchairs with a dynamically stable mobile manipulator. Wheelchairs are a type of nonholonomic cart system, maneuvering such systems with mobile manipulators (MM) is challenging mostly due to the following reasons: 1) These systems feature nonholonomic constraints and considerably varying inertial parameters that require online identification and adaptation. 2) These systems are widely used in human-centered environments, which demand the MM to operate in potentially crowded spaces while ensuring compliance for safe physical human-robot interaction (pHRI). We propose a control framework that plans whole-body motion based on quasi-static analysis to maneuver heavy nonholonomic carts while maintaining overall compliance. We validated our approach experimentally by maneuvering a wheelchair with a bimanual mobile manipulator, the CMU ballbot. The experiments demonstrate the proposed framework is able to track desired wheelchair velocity with loads varying from 11.8 kg to 79.4 kg at a maximum linear velocity of 0.45 m/s and angular velocity of 0.3 rad/s. Furthermore, we verified that the proposed method can generate human-like motion smoothness of the wheelchair while ensuring safe interactions with the environment.

In this paper, we present a planning and control framework for dynamic, whole-body motions for dynamically stable shape-accelerating mobile manipulators. This class of robots are inherently unstable and require careful coordination between the upper and lower body to maintain balance while performing arm motion tasks. Solutions to this problem either use a complex, full-body nonlinear dynamic model of the robot or a highly simplified model of the robot. Here we explore the use of centroidal dynamics which has recently become a popular approach for designing balancing controllers for humanoid robots. We describe a framework where we first solve a trajectory optimization problem offline. We define balancing for a ballbot in terms of the centroidal momentum instead of other approaches like ZMP or angular velocity that are more commonly used. The generated motion is tracked using a PD-PID cascading balancing controller for the body and torque controller for the arms. We demonstrate that this framework is capable of generating dynamic motion plans and control inputs with examples on the CMU ballbot, a single-spherical-wheeled balancing mobile manipulator.

A control algorithm is developed to enable dynamically stable spherical-wheel robots (ballbots) with arms to detect a heavy object of unknown mass, navigate to it, lift it, transport it, and place it in a desired location semi-autonomously. Previous work has successfully demonstrated two-wheeled dynamically stable mobile manipulator robots transporting heavy objects. We report here the first ballbot to reliably achieve such a task. A successful semi-autonomous lift and transport of a 15 kg heavy box whose actual mass was unknown was achieved using a combination of feedforward and feedback control laws based on a quasi-static center of mass computation. The ballbot's pan and tilt sensor turret tracked fiducial markers on the box. Ballbot-to-human and human-to-ballbot exchanges of a 10 kg heavy object was achieved while dynamically balancing.

Inertial reorientation of airborne articulated bodies has been an active area of research in the robotics community, as this behavior can help guide dynamic robots to a safe landing with minimal damage. The main objective of this work is emulating the aggressive and large angle correction maneuvers, like somersaults, that are performed by human divers. To this end, a planar three link robot, called DiverBot, is proposed. By considering a gravity-free scenario, a local connection is obtained between joint angles and the body orientation, resulting in a reduction in the system dynamics. An optimal control policy applied on this reduced configuration space yielded diving maneuvers that are dynamically feasible. Numerical results show that the DiverBot can execute one somersault without drift and multiple somersaults with minimal drift.