Elizabeth A. Croft

Jerk-bounded manipulator trajectory planning: design for real-time applications

An online method for obtaining smooth, jerk-bounded trajectories has been developed and implemented. Jerk limitation is important in industrial robot applications, since it results in improved path tracking and reduced wear on the robot. The method described herein uses a concatenation of fifth-order polynomials to provide a smooth trajectory between two way points. The trajectory approximates a linear segment with parabolic blends trajectory. A sine wave template is used to calculate the end conditions (control points) for ramps from zero acceleration to nonzero acceleration. Joining these control points with quintic polynomials results in a controlled quintic trajectory that does not oscillate, and is near time optimal for the jerk and acceleration limits specified. The method requires only the computation of the quintic control points, up to a maximum of eight points per trajectory way point. This provides hard bounds for online motion algorithm computation time. A method for blending these straight-line trajectories over a series of way points is also discussed. Simulations and experimental results on an industrial robot are presented.

Pre-collision safety strategies for human-robot interaction

Safe planning and control is essential to bringing human-robot interaction into common experience. This paper presents an integrated human−robot interaction strategy that ensures the safety of the human participant through a coordinated suite of safety strategies that are selected and implemented to anticipate and respond to varying time horizons for potential hazards and varying expected levels of interaction with the user. The proposed planning and control strategies are based on explicit measures of danger during interaction. The level of danger is estimated based on factors influencing the impact force during a human-robot collision, such as the effective robot inertia, the relative velocity and the distance between the robot and the human.A second key requirement for improving safety is the ability of the robot to perceive its environment, and more specifically, human behavior and reaction to robot movements. This paper also proposes and demonstrates the use of human monitoring information based on vision and physiological sensors to further improve the safety of the human robot interaction. A methodology for integrating sensor-based information about the users position and physiological reaction to the robot into medium and short-term safety strategies is presented. This methodology is verified through a series of experimental test cases where a human and an articulated robot respond to each other based on the humans physical and physiological behavior.

Haptic rendering of rigid contacts using impulsive and penalty forces

A new simulation approach is proposed to improve the stability and the perceived rigidity of contacts during haptic interaction with multirigid body virtual environments. The approach computes impulsive forces upon contact and penalty and friction forces during contact. The impulsive forces are derived using a new multiple collision resolution method that never increases the kinetic energy of the system. When new contacts arise, the impulsive forces generate large hand accelerations without requiring increased contact stiffness and damping. Virtual objects and linkages are regarded as points in the configuration space, and no distinction is made between them in the proposed approach.

Real-time safety for human–robot interaction☆

This paper presents a strategy for ensuring safety during human-robot interaction in real time. A measure of danger during the interaction is explicitly computed, based on factors affecting the impact force during a potential collision between the human and the robot This danger index is then used as an input to real-time trajectory generation when the index exceeds a predefined threshold. The danger index is formulated to produce stable motion in the presence of multiple surrounding obstacles. A motion strategy to minimize the danger index is developed for articulated multi degree of freedom robots. Simulations and experiments demonstrate the efficacy of this approach

The reduction of stick-slip friction in hydraulic actuators

The stick-slip friction phenomenon is observed near zero relative velocity, during the transition from static to dynamic friction, when static friction is greater than dynamic friction. This nonlinear change in friction force over a small change in velocity results in difficulties in achieving accurate and repeatable position control. In some cases, the actuator position controller reaches a limit cycle (hunting effect). Friction compensation at low speeds has traditionally been approached through various control techniques. This paper proposes an alternative solution, namely, friction avoidance. By rotating the piston and rod, the Stribeck region of the friction-velocity curve is avoided and the axial friction opposing the piston movement is approximately linearized. Simulation and experimental results are presented to validate this approach.

Modeling and Control of Contouring Errors for Five-Axis Machine Tools—Part I: Modeling

Aerospace, die, and mold industries utilize parts with sculptured surfaces, which are machined on five-axis computer numerical controlled machine tools. Accurate path tracking for contouring is not always possible along the desired space curves due to the loss of joint coordination during the five-axis motion. This two-part paper presents modeling and robust control of contouring errors for five-axis machines. In Part I, two types of contouring errors are defined by considering the normal deviation of tool tip from the reference path, and by the normal deviation of the tool axis orientation from the reference orientation trajectory defined in the spherical coordinates. Overall contouring errors are modeled during five-axis motion that has simultaneous translation and rotary motions. The coupled kinematic configuration and the rigid body dynamics of all five drives are considered. The contouring error model is experimentally validated on a five-axis machine tool. The error model developed in this paper is then used for simultaneous, real-time robust control of all five drives in Part II.

Full-State Tracking Control for Flexible Joint Robots With Singular Perturbation Techniques

This paper proposes a practical method to realize multivariable full-state tracking control for industrial robots with elastic joints. Unlike existing methods, the proposed method does not require high-order derivatives of the link states such as acceleration and jerk. Therefore, the proposed method does not suffer from chatter related to inaccurate estimation of high-order derivatives. The method is derived by adopting a singular perturbation technique. A decoupled error dynamics is achieved by two decoupling control loops: a fast loop that controls the deflection error and a slow loop for tracking control on the link side. Our stability analysis based on a linear system shows that the proposed control system is stable as long as the fast system is at least twice as fast as the slow system. A practical method to select the gain is also presented such that the closed-loop poles are placed at the desired locations. In simulation, we compare the proposed method with feedback linearization. The results indicate that in an ideal scenario the proposed method can obtain a similar performance as feedback linearization. However, the proposed method obtains a superior performance in a realistic scenario. A real-world experiment with a six degree-of-freedom commercial industrial robot is carried out to further validate our approach.

Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing

In this paper we provide empirical evidence that using humanlike gaze cues during human-robot handovers can improve the timing and perceived quality of the handover event. Handovers serve as the foundation of many human-robot tasks. Fluent, legible handover interactions require appropriate nonverbal cues to signal handover intent, location and timing. Inspired by observations of human-human handovers, we implemented gaze behaviors on a PR2 humanoid robot. The robot handed over water bottles to a total of 102 naïve subjects while varying its gaze behaviour: no gaze, gaze designed to elicit shared attention at the handover location, and the shared attention gaze complemented with a turntaking cue. We compared subject perception of and reaction time to the robot-initiated handovers across the three gaze conditions. Results indicate that subjects reach for the offered object significantly earlier when a robot provides a shared attention gaze cue during a handover. We also observed a statistical trend of subjects preferring handovers with turn-taking gaze cues over the other conditions. Our work demonstrates that gaze can play a key role in improving user experience of human-robot handovers, and help make handovers fast and fluent.Categories and Subject Descriptors I.2.9 [Robotics]: Operator interfaces, Commercial robots and applications; H.1.2 [User/Machine Systems]: Human FactorsGeneral TermsExperimentation, Design, Human Factors, Verification.

Gestures for industry: intuitive human-robot communication from human observation

Human-robot collaborative work has the potential to advance quality, efficiency and safety in manufacturing. In this paper we present a gestural communication lexicon for human-robot collaboration in industrial assembly tasks and establish methodology for producing such a lexicon. Our user experiments are grounded in a study of industry needs, providing potential real-world applicability to our results. Actions required for industrial assembly tasks are abstracted into three classes: part acquisition, part manipulation, and part operations. We analyzed the communication between human pairs performing these subtasks and derived a set of communication terms and gestures. We found that participant-provided gestures are intuitive and well suited to robotic implementation, but that interpretation is highly dependent on task context. We then implemented these gestures on a robot arm in a human-robot interaction context, and found the gestures to be easily interpreted by observers. We found that observation of human-human interaction can be effective in determining what should be communicated in a given human-robot task, how communication gestures should be executed, and priorities for robotic system implementation based on frequency of use.

Anxiety detection during human-robot interaction

This paper describes an experiment to determine the feasibility of using physiological signals to determine the human response to robot motions during direct human-robot interaction. A robot manipulator is used to generate common interaction motions, and human subjects are asked to report their response to the motions. The human physiological response is also measured. Motion paths are generated using a classic potential field planner and a safe motion planner, which minimizes the potential collision force along the path. A fuzzy inference engine is developed to estimate the human response based on the physiological measures. Results show that emotional arousal can be detected using physiological signals and the inference engine. Comparison of initial results between the two planners shows that subjects report less anxiety and surprise with the safe planner for high planner speeds.