S. Macfarlane

Bio: S. Macfarlane is an academic researcher. The author has contributed to research in topics: Acceleration & Quintic function. The author has an hindex of 1, co-authored 1 publications receiving 355 citations.

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

Abstract: 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.

Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events

Abstract: This paper introduces a new method for motion-trajectory generation of mechanical systems with multiple degrees of freedom (DOFs). The key feature of this new concept is that motion trajectories are generated online, i.e., within every control cycle, typically every millisecond. This enables systems to react instantaneously to unforeseen and unpredictable (sensor) events at any time instant and in any state of motion. As a consequence, (multi)sensor integration in robotics, in particular the development of control systems enabling sensor-guided and sensor-guarded motions, becomes greatly simplified. We introduce a class of online trajectory-generation algorithms and present the mathematical basics of this new approach. The algorithms presented here consist of three steps: calculation of the minimum synchronization time for all DOFs, synchronization of all DOFs, and calculation of output values. The theory is followed by real-world experimental results indicating new possibilities in robot-motion control.

Pre-collision safety strategies for human-robot interaction

Abstract: 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 user's 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 human's physical and physiological behavior.

Feed-rate optimization with jerk constraints for generating minimum-time trajectories

Abstract: Competitive pressure requires manufacturers to simultaneously address increasingly stringent constraints on both productivity and quality. From the perspective of numerically controlled (NC) machine tools, this means higher machining performance in terms of speed and accuracy. Conventional approaches to programming NC operations involve selecting a constant feedrate for a given operation to produce acceptable performance (operation time and contouring accuracy). In this paper, we examine the possibility of scheduling or varying the feedrate by taking into consideration the geometry of the contour that the machine is expected to follow and the physical capabilities of the machine (i.e., its maximum velocity, acceleration and jerk constraints). Previous work by the authors has addressed the efficient, off-line computation of time-optimal trajectories with constraints on velocity and acceleration. This paper introduces additional constraints on the permissible jerk (rate of change of acceleration) on the machine's axis. From a practical perspective, excessive jerk leads to excitation of vibrations in components in the machine assembly, accelerated wear in the transmission and bearing elements, noisy operations and large contouring errors at discontinuities (such as corners) in the machining path. The introduction of jerk into the feedrate scheduling problem makes generating computationally efficient solutions while simultaneously guaranteeing optimality a challenging problem. This paper approaches this problem as an extension of our previous bi-directional scan algorithm [23] , [29] . A new acceleration-continuation procedure is added to the feedrate optimization algorithm to address jerk constraints and remove discontinuities in the acceleration profile. The algorithm maintains computational efficiency and supports the incorporation of a variety of state-dependent (such as position, velocity, acceleration and jerk) constraints. By carefully organizing the local search and acceleration continuity enforcing steps, a globally optimal solution is achieved. Singularities, or critical points, and critical curves on the trajectory, which are difficult to deal within optimal control approaches, are treated in a natural way in this algorithm. Several application examples and tests are performed to verify the effectiveness of this approach for high-speed contouring.

Synthesizing Robot Motions Adapted to Human Presence A Planning and Control Framework for Safe and Socially Acceptable Robot Motions

Abstract: With robotics hardware becoming more and more safe and compliant, robots are not far from entering our homes. The robot, that will share the same environment with humans, will be expected to consider the geometry of the interaction and to perform intelligent space sharing.