A polyhedral friction cone is a set of reaction wrenches that an object can experience whilst in contact with its environment. This polyhedron is a powerful tool to control an object’s motion and interaction with the environment. It can be derived analytically, upon knowledge of object and environment geometries, contact point locations and friction coefficients. We propose to estimate the polyhedral friction cone so that a priori knowledge of these quantities is no longer required. Additionally, we introduce a solution to transform the estimated friction cone to avoid re-estimation while the object moves. We present an analysis of the estimated polyhedral friction cone and demonstrate its application for manipulating an object in simulation and with a real robot.

A proportional-integral-derivative (PID) controller is a control loop feedback mechanism widely employed in industrial control systems. The parameters tuning is a sticking point, having a great effect on the control performance of a PID system. There is no perfect rule for designing controllers, and finding an initial good guess for the parameters of a well-performing controller is difficult. In this paper, we develop a knowledge-based particle swarm optimization by incorporating the dynamic response information of PID into the optimizer. Prior knowledge not only empowers the particle swarm optimization algorithm to quickly identify the promising regions, but also helps the proposed algorithm to increase the solution precision in the limited running time. To benchmark the performance of the proposed algorithm, an electric pump drive and an automatic voltage regulator system are selected from industrial applications. The simulation results indicate that the proposed algorithm with a newly proposed performance index has a significant performance on both test cases and outperforms other algorithms in terms of overshoot, steady state error, and settling time.

This paper introduces dynamic manipulability of the center of mass (CoM) as a metric to measure robots' physical abilities to accelerate their CoMs in different directions. By decomposing the effects of velocity dependent constraints, such as unilateral contacts and friction cones, CoM dynamic manipulability is defined as a velocity independent metric which depends only on robot's configuration and inertial parameters. Thus, this metric is independent of any choice of controller and expresses only physical abilities of robots. This important property makes the proposed metric a proper tool to study, analyse and design current and future robots. The outcome of the CoM dynamic manipulability analysis in this paper is an ellipsoid in the CoM acceleration space which graphically shows accessible points due to the unit weighted norm of joint torques. Physical meanings and concepts of two reasonable choices for the weighting matrix, which is used in the weighted norm of joint torques, are discussed and illustrative examples are presented. Since the proposed metric measures physical ability to accelerate the CoM, it is claimed to be a suitable tool to study balance ability of legged robots.

This paper proposes a momentum-based balancing controller for robots which have non-rigid contacts with their environments. This controller regulates both linear momentum and angular momentum about the center of mass of the robot by controlling the contact forces. Compliant contact models are used to determine the contact forces at the contact points. Simulation results show the performance of the controller on a four-link planar robot standing on various compliant surfaces while unknown external forces in different directions are acting on the center of mass of the robot.

This paper presents an angular momentum based controller to control the balancing motion of a spatial underactuated robot with three degrees of under-actuation. The control algorithm is based on the idea of decoupling the robot's motion instantaneously into bending and swivelling motions. This property of the robot is obtained by using a constant velocity joint as the 2-DoF active joint of the robot. Simulation results show the performance of the controller during some interesting motions of the robot such as straightening, crouching and reorienting motions. The last two motions, which are the results of decoupling the robot's motion, are demonstrated here for the first time.

This paper presents a new nonlinear model of the normal force that arises during compliant contact between two spheres, or between a sphere and a flat plate. It differs from a well-known existing model by only a single term. The advantage of the new model is that it accurately predicts the measured values of the coefficient of restitution between spheres and plates of various materials, whereas other models do not.

In this paper, a new control algorithm is presented for implementing hopping and balancing motions on a planar hopping machine with a single actuated revolute joint. Starting with a simple control algorithm for balancing, it is extended to perform trajectory-tracking maneuvers, which enables it to perform the crouching, lift-off and flight phases of a single hop, as well as re-balancing after landing. Simulation results are presented showing that the control system works well, and that it is not significantly affected by small amounts of slipping between the foot and the ground.