A robot making contact with an environment or human presents potential safety risks, including excessive collision force. While experiments on the effect of robot inertia, relative velocity, and interface stiffness on collision are in literature, analytical models for maximum collision force are limited to a simplified mass-spring robot model. This simplified model limits the analysis of control (force/torque, impedance, or admittance) or compliant robots (joint and end-effector compliance). Here, the Sobolev norm is adapted to be a system norm, giving rigorous bounds on the maximum force on a stiffness element in a general dynamic system, allowing the study of collision with more accurate models and feedback control. The Sobolev norm can be found through the H2norm of a transformed system, allowing efficient computation, connection with existing control theory, and controller synthesis to minimize collision force. The Sobolev norm is validated, first experimentally with an admittance-controlled robot, then in simulation with a linear flexible-joint robot. It is then used to investigate the impact of control, joint flexibility and end-effector compliance on collision, and a trade-off between collision performance and environmental estimation uncertainty is shown.

Interactive robots offer improved performance in tasks with environmental uncertainty, but accommodating environment input weakens predictions of contact force or position trajectories, making the identification of subtask completion or faults difficult. This paper develops a task monitoring approach for complex assembly tasks that involve transitions between discrete environment dynamic modes. In semi-structured environments, these dynamic modes and their transitions are approximately known a priori, allowing task monitoring through estimation of the current mode and fault detection as a deviation from expected, desired dynamic mode transitions. This allows a more natural description of many interactive tasks, improving robustness to variations in force or position trajectories that impedance control seeks to address. The ability of impedance and admittance controlled robots to identify their environment is investigated, making consideration of joint and end-effector physical compliance. Prior information on environment dynamics and mode transitions allow recursive estimates of dynamic mode suitable for online use, under both full state knowledge and only force/position measurements. Experiments with an admittance controlled robot in a gear assembly task validate the approach.

Human dynamic models are useful in design of physical human-robot and human-robot-environment interaction: informing choice of robot impedance, motivating relaxations to passivity-based safety constraints, and allowing online inference to user intent. Designing for performance objectives such as stable well-damped contact transitions also requires nominal models, but the use of human models in controller design is limited. Established approaches to identify human dynamics apply position or force perturbation and measure the corresponding response, mostly to validate neuromuscular hypotheses on motor control, which raises questions about their transferability to human-led collaboration. Here, human dynamics are identified in a task which closely resembles the final application, where the human leads the robot into contact with a (virtual) wall. This paper investigates the impact of human dynamics on coupled system behavior, and establishes a general framework for identification in human-led scenarios, making consideration of unmeasured human input. Experiments with different stiffness environments allow inference to human dynamics, and characterize the range of human dynamics which can be modulated by the user.

This paper gives an introduction to the process of an experimental project in pertaining to the planning and integrating of a human-robot interactive stone carving system. The process includes an analysis of manual stone carving by a professional sculptor, a risk assessment of the projected robotic assistant system resulting in the safety concepts, a design of a tool carrier with force sensors and the human-machine interface. A standard industrial robot was selected and enhanced with extensive periphery to build up the intelligent tool carrier. Besides scientific results regarding work space and contact force suitable for human-robot collaboration, this paper presents the sculptural aspects within the experiment project. The professional scluptor evaluated the results as beyond manual processing.

The paper presents robotic approach to life-cycle testing based on advanced compliance control algorithms. This strategy has been demonstrated as meaningful testing approach considering repeatability and reproducibility. Moreover, developed testing procedures mimic human motion and ensure human-like testing conditions. That is a crucial advantage over simple testing machines or convenient industrial robots, which can not realize comparable system behavior. Application of a variable-impedance control strategy provides a feasible approach in reproducing human behavior and realizing faster life-cycle test execution.

The primary concern in haptic systems is to achieve stable interaction under any operating conditions and for all simulated virtual environments, without unwanted oscillations that degrade virtual surface rendering. This paper represents a novel approach for controlling interaction with a haptic interface based on robust control design framework established for the control synthesis of interaction between an impedance-controlled robot and a passive environment. Initial experiments results have demonstrated advantages, high performance in interaction with a very stiff environment and reliability of the new algorithms.

A widespread application of impedance control in industrial robotic systems is still a challenging problem. One of limitations is the absence of a widely-accepted framework for the synthesis of the impedance control parameters that ensure stability of both contact transition and interaction processes and guarantee desired contact performance. The existing design procedures based on robot passivity appear to be exceedingly conservative in applications in which the interaction between an industrial robot and a stiff environment should be controlled. The proposed new interaction stability paradigm ensures contact stability during all phases of interaction. Moreover, the new design framework realizes low-impedance performance allowing considerable reduction of high apparent industrial robot inertia and stiffness. The novel stability criteria are established based on robust control theory and take into account estimates of environmental stiffness, tolerating thereby large uncertainties and variations in industrial environments. These criteria are proved by extensively testing in industrial and space robots and have been recently extended to control synthesis of human robot interaction systems (haptic admittance displays and rehabilitation robots).

This paper presents a novel robotic prototype for advanced gait rehabilitation. This system integrates sophisticated robotic technology with control algorithms. The robot opens up new possibilities for the field of rehabilitation for restoring posture balancing and gait motoric functions. The paper provides an overview of the system's fundamental components, such as mechanical structure, patient-machine interface, sensory systems, control algorithms, etc. The results of some initial experiments also are included.

This work represents a novel cobotic system with differential CVT. The new system is significantly cheaper, simpler to control and more efficient than cobots with S-CVTs. Both path-guidance and power-assist functions can simply be realized with the new system. The paper addresses basic cobot structures, kinematic and dynamic models, as well as control algorithms. Kinematic singularity problems, which in cobotic systems appear to be more complex than in robotic structures, are also considered. Experiments with the first industrial cobot prototype, which is implemented in a SCARA manipulator arm, demonstrate the performance of novel singularity avoidance and control algorithms.

Acceleration in redundancy resolution has been achieved by model-based learning. Parameterized joint motions generated by pseudoinverse of parameterized motion primitives in operational space are taken as learning examples. The method of successive approximations (SA) as a function approximator generalizes given examples resulting in a parameterized model, termed redundancy resolution skill. The SA method results in an analytical solution of joint motions. This particular property enables extension of the universality of skills to tasks never experienced by learning. Moreover, a proper addressing of skills output results in paths completely different from learned ones. In practice, this means that a segment as a motion primitive suffices in acquiring skill in the learning domain. The example emphasises this property of SA-based redundancy resolution. Highly compressed skill, acquired on segments only, is applied in RR along two test-trajectories-an 'H'-character and a rosette. The gained acceleration of RR recommends this procedure for online redundant robot control and easy robot programming.

This paper presents a simple and computationally efficient control scheme for improving the constrained motion control performance of an impedance controlled industrial robot interacting with an uncertain stationary environment. The proposed method combines the model-based and fuzzy control techniques. The scheme consists of three main components: a basic infernal position control loop, an external impedance controller realizing target model behavior, and a fuzzy adaptation mechanism that modifies impedance parameters according to the difference between the actual and desired force responses. Several experiments performed on an industrial robot are conducted to demonstrate the performance of the new approach. The comparison with conventional impedance control laboratory experiments illustrates advantages and drawbacks of the proposed scheme.

Describes the algorithms for the integration of a position based impedance control scheme in conventional industrial robot control systems. The new control functions which support programming, specification and monitoring compliance motion control are presented. These control functions constitute a powerful framework for executing most contact tasks with relatively low efforts. The experiments with SPARCO control systems and the CAT arm are included to demonstrate the performance of the control algorithms.

Contact stability has been considered based on simplified linearized models of a robot and its environment. It is shown that the most crucial parameter for contact stability is the target damping ratio. When a high compliance is required, the stability boundary requires a significantly overdamped impedance to ensure a stable contact with a stiff environment. These conditions for a SISO system are defined in the analytic form. Obtained minimal damping ratio values are significantly lower than those previously proposed in the literature.

A common way to identify the robot dynamics is to use a linear model structure in relation to the parameters and standard least-square (LS) techniques. These techniques are sensitive to noise measurements and error modeling, so that it is necessary that the trajectory is "exciting enough" to provide an accurate estimate of the parameters. This paper addresses criteria of exciting trajectories for robot dynamics identification. An optimum criterion, which corresponds to the G-optimum criteria known from the literature, is derived from the "true system" concept. It also shows that through exploitation of the model structure properties, the design of G-optimal experiments are made considerably easier. A G-optimal experiment for a two degrees of freedom SCARA robot is designed to show the simplicity and efficiency of these approaches.

The contact stability has been considered based on simplified linearized models of robot and environment. It is shown that the most crucial parameter for contact stability is the target damping ratio. When a high compliance is required the stability boundary conditions require significantly overdamped impedance behavior to ensure a stable contact with a stiff environment. These conditions for a SISO system are defined in the analytic form. Obtained minimal damping ratio values are significantly lower than those previously proposed in the literature.

This paper presents a new position-based force/impedance control scheme which provides a feasible and reliable solution for performing contact tasks in industrial robotic systems. The control scheme consists of an outer implicit force control loop closed around an internal position-based impedance control loop. The enclosed experiment demonstrates performance of the proposed compliant control concepts in performing a relatively simple contact task with a conventional industrial robot.