Bojan Nemec

Kinematic control algorithms for on-line obstacle avoidance for redundant manipulators

The paper deals with kinematic control algorithms for on-line obstacle avoidance which allow a kinematically redundant manipulator to move in an unstructured environment without colliding with obstacles. The presented approach is based on the redundancy resolution at the velocity level. The primary task is determined by the end-effector trajectories and for obstacle avoidance the internal motion of the manipulator is used. The obstacle avoiding motion is defined in one-dimensional operational space and, hence, the system has less singularities making implementation easier. Instead of the exact pseudoinverse solution we propose an approximate one which is computationally more efficient and allows us to consider many simultaneously active obstacles without any problems. The fast cycle times of the numerical implementation enable use of the algorithm in real-time control. For illustration, some simulation results of a highly redundant planar manipulator moving in an unstructured and time-varying environment and experimental results of a four link planar manipulator are given.

Coupling Movement Primitives: Interaction With the Environment and Bimanual Tasks

The framework of dynamic movement primitives (DMPs) contains many favorable properties for the execution of robotic trajectories, such as indirect dependence on time, response to perturbations, and the ability to easily modulate the given trajectories, but the framework in its original form remains constrained to the kinematic aspect of the movement. In this paper, we bridge the gap to dynamic behavior by extending the framework with force/torque feedback. We propose and evaluate a modulation approach that allows interaction with objects and the environment. Through the proposed coupling of originally independent robotic trajectories, the approach also enables the execution of bimanual and tightly coupled cooperative tasks. We apply an iterative learning control algorithm to learn a coupling term, which is applied to the original trajectory in a feed-forward fashion and, thus, modifies the trajectory in accordance to the desired positions or external forces. A stability analysis and results of simulated and real-world experiments using two KUKA LWR arms for bimanual tasks and interaction with the environment are presented. By expanding on the framework of DMPs, we keep all the favorable properties, which is demonstrated with temporal modulation and in a two-agent obstacle avoidance task.

Orientation in Cartesian Space Dynamic Movement Primitives

Dynamic movement primitives (DMPs) were proposed as an efficient way for learning and control of complex robot behaviors. They can be used to represent point-to-point and periodic movements and can be applied in Cartesian or in joint space. One problem that arises when DMPs are used to define control policies in Cartesian space is that there exists no minimal, singularity-free representation of orientation. In this paper we show how dynamic movement primitives can be defined for non minimal, singularity free representations of orientation, such as rotation matrices and quaternions. All of the advantages of DMPs, including ease of learning, the ability to include coupling terms, and scale and temporal invariance, can be adopted in our formulation. We have also proposed a new phase stopping mechanism to ensure full movement reproduction in case of perturbations.

Force control of redundant robots in unstructured environment

In this paper, a method for force control of redundant robots in an unstructured environment is proposed. We assume that the obstacles are not known in advance. Hence, the robot arm has to be compliant with the environment while tracking the desired position and force at the end-effector. First, the dynamic properties of the internal motion of redundant manipulators are considered. The motion is decoupled into the end-effector motion and the internal motion. Next, the dynamic model of a redundant manipulator is derived. Special attention is given to the inertial properties of the system in the space where internal motion is taking place; the authors define a null-space effective inertia and its inverse. Finally, a control method is proposed which completely decouples the motion of the manipulator into the task-space motion and the internal motion and enables the selection of dynamic characteristics in both subspaces separately. The proposed method is verified with simulation and with experimental results of a four-degrees-of-freedom planar redundant robot.

Action sequencing using dynamic movement primitives

General-purpose autonomous robots must have the ability to combine the available sensorimotor knowledge in order to solve more complex tasks. Such knowledge is often given in the form of movement primitives. In this paper, we investigate the problem of sequencing of movement primitives. We selected nonlinear dynamic systems as the underlying sensorimotor representation because they provide a powerful machinery for the specification of primitive movements. We propose two new methodologies which both ensure that consecutive movement primitives are joined together in a continuous way (up to second-order derivatives). The first is based on proper initialization of the third-order dynamic motion primitives and the second uses online Gaussian kernel functions modification of the second-order dynamic motion primitives. Both methodologies were validated by simulation and by experimentally using a Mitsubishi PA-10 articulated robot arm. Experiments comprehend pouring, table wiping, and carrying a glass of liquid.

Null space velocity control with dynamically consistent pseudo-inverse

Null space velocity control is essential for achieving good behaviour of a redundant manipulator. Using the dynamically consistent pseudo-inverse, the task and null space motion and forces are decoupled. The paper presents a globally stable null space velocity controller and the gradient projection technique in conjunction with the dynamically consistent pseudo-inverse. The physical meaning and influence of the compensation terms in null the space velocity controller are explained. The performance of the proposed null space controller is tested on 4. d.o.f planar redundant manipulator interacting with the environment.

Aerodynamic drag is not the major determinant of performance during giant slalom skiing at the elite level.

This investigation was designed to (a) develop an individualized mechanical model for measuring aerodynamic drag (Fd) while ski racing through multiple gates, (b) estimate energy dissipation (Ed) caused by Fd and compare this to the total energy loss (Et), and (c) investigate the relative contribution of Ed/Et to performance during giant slalom skiing (GS). Nine elite skiers were monitored in different positions and with different wind velocities in a wind tunnel, as well as during GS and straight downhill skiing employing a Global Navigation Satellite System. On the basis of the wind tunnel measurements, a linear regression model of drag coefficient multiplied by cross‐sectional area as a function of shoulder height was established for each skier (r > 0.94, all P < 0.001). Skiing velocity, Fd, Et, and Ed per GS turn were 15–21 m/s, 20–60 N, −11 to −5 kJ, and −2.3 to −0.5 kJ, respectively. Ed/Et ranged from ∼5% to 28% and the relationship between Et/vin and Ed was r = −0.12 (all NS). In conclusion, (a) Fd during alpine skiing was calculated by mechanical modeling, (b) Ed made a relatively small contribution to Et, and (c) higher relative Ed was correlated to better performance in elite GS skiers, suggesting that reducing ski–snow friction can improve this performance.

Compensation of velocity and/or acceleration joint saturation applied to redundant manipulator

The article describes a new method for velocity/acceleration redistribution in order to compensate joint velocity and/or acceleration saturation. The method is designed for redundant manipulators. When some of the joint velocities/accelerations are in saturation other joints compensate for the lack of the velocity and the velocity in the task space remains unchanged. Without the compensation the task space error would appear. Using the compensation method we can achieve maximal velocity/acceleration in the task space while preserving joint velocity/acceleration within limits. The method is also appropriate to compensate a torque saturation. Additionally, we have introduced a condition that shows if the compensation is kinematically and mathematically possible or not.

Adaptation of manipulation skills in physical contact with the environment to reference force profiles

We propose a new methodology for learning and adaption of manipulation skills that involve physical contact with the environment. Pure position control is unsuitable for such tasks because even small errors in the desired trajectory can cause significant deviations from the desired forces and torques. The proposed algorithm takes a reference Cartesian trajectory and force/torque profile as input and adapts the movement so that the resulting forces and torques match the reference profiles. The learning algorithm is based on dynamic movement primitives and quaternion representation of orientation, which provide a mathematical machinery for efficient and stable adaptation. Experimentally we show that the robot’s performance can be significantly improved within a few iteration steps, compensating for vision and other errors that might arise during the execution of the task. We also show that our methodology is suitable both for robots with admittance and for robots with impedance control.

Analysis of human peg-in-hole executions in a robotic embodiment using uncertain grasps

In this paper, we perform a quantitative and qualitative analysis of human peg-in-hole operations in a tele-operating setting with a moderate degree of dexterity. Peg-in-hole operation with different starting configurations are performed with the aim to derive a strategy for performing such actions with a robot. The robot is a 6 DoF robot arm with the dexterous 3 finger SDH-2 gripper. From the extracted data, we can distill important insights about (1) feasible grasps depending on the pegs pose, (2) the object trajectory, (3) the occurrence of a particular force-torque pattern during the monitoring of the action and (4) an appropriate insertion strategy. At the end of the paper, we discuss consequences for using these insights for deriving algorithms for robot execution of peg-in-hole actions with dexterous manipulators.