Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type

Human-guided Swarms: Impedance Control-inspired Influence in Virtual Reality Environments

Prior works in human-swarm interaction (HSI) have sought to guide swarm behavior towards established objectives, but may be unable to handle specific scenarios that require finer human supervision, variable autonomy, or application to large-scale swarms. In this paper, we present an approach that enables human supervisors to tune the level of swarm control, and guide a large swarm using an assistive control mechanism that does not significantly restrict emergent swarm behaviors. We develop this approach in a virtual reality (VR) environment, using the HTC Vive and Unreal Engine 4 with AirSim plugin. The novel combination of an impedance control-inspired influence mechanism and a VR test bed enables and facilitates the rapid design and test iterations to examine trade-offs between swarming behavior and macroscopic-scale human influence, while circumventing flight duration limitations associated with battery-powered small unmanned aerial system (sUAS) systems. The impedance control-inspired mechanism was tested by a human supervisor to guide a virtual swarm consisting of 16 sUAS agents. Each test involved moving the swarm's center of mass through narrow canyons, which were not feasible for a swarm to traverse autonomously. Results demonstrate that integration of the influence mechanism enabled the successful manipulation of the macro-scale behavior of the swarm towards task completion, while maintaining the innate swarming behavior.Comment: 11 pages, 5 figures, preprin

A fault detection and isolation system for cooperative manipulators

The problem of fault detection and isolation (FDI) in cooperative manipulators is addressed in this paper. Four FDI procedures are developed to deal with free-swinging joint faults, locked joint faults, incorrectly measured joint position, and incorrectly measured joint velocity. Free-swinging and locked joint faults are isolated via neural networks. For each arm, a Multilayer Perceptron (MLP) is used to reproduce the dynamics of the fault-free robot. The outputs of each MLP are compared to the actual joint velocities in order to generate a residual vector which is then classified by an RBF network. The remaining faults are isolated based on the kinematic constraints imposed on the cooperative system. Results obtained via simulations and via an actual cooperative manipulator robot are presented

Impedance control for legged robots: an insight into the concepts involved

The application of impedance control strategies to modern legged locomotion is analyzed, paying special attention to the concepts behind its implementation which is not straightforward. In order to implement a functional impedance controller for a walking mechanism, the concepts of contact, impact, friction, and impedance have to be merged together. A literature review and a comprehensive analysis are presented compiling all these concepts along with a discussion on position-based versus force-based impedance control approaches, and a theoretical model of a robotic leg in contact with its environment is introduced. A theoretical control scheme for the legs of a general legged robot is also introduced, and some simulations results are presented

Human-Robot Team Interaction Through Wearable Haptics for Cooperative Manipulation

The interaction of robot teams and single human in teleoperation scenarios is beneficial in cooperative tasks, for example the manipulation of heavy and large objects in remote or dangerous environments. The main control challenge of the interaction is its asymmetry, arising because robot teams have a relatively high number of controllable degrees of freedom compared to the human operator. Therefore, we propose a control scheme that establishes the interaction on spaces of reduced dimensionality taking into account the low number of human command and feedback signals imposed by haptic devices. We evaluate the suitability of wearable haptic fingertip devices for multi-contact teleoperation in a user study. The results show that the proposed control approach is appropriate for human-robot team interaction and that the wearable haptic fingertip devices provide suitable assistance in cooperative manipulation tasks

Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies

In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in $SE(3)$. The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller's behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller's performance using numerical simulations of a manipulation task in 3D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions