Reference Spreading: Tracking Performance for Impact Trajectories of a 1DoF Setup

Abstract

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Robot control for simultaneous impact tasks via QP based reference spreading

“…with threshold ǫ. In real-life robotic applications, switching will occur based on impact detection, for example through jump-aware filtering [29], as is used in the experimental validation of reference spreading in [19].…”

“…The switching from ante-to post-impact control mode is done based on detection of the impact, instead of being tied to the nominal impact time, to remove the peak in the velocity error, which can lead to unpredictable behavior. Experimental validation of reference spreading on a physical setup has been reported in [19]. When dealing with robotic and mechanical systems, reference spreading is applied by modeling contacts as rigid and impacts as inelastic, following the theory of multibody dynamics and nonsmooth mechanics [20], [21] to capture the configuration dependent velocity jumps by means of impact laws [17].…”

Modeling, analysis and control of robot–object nonsmooth underactuated Lagrangian systems: A tutorial overview and perspectives

“…More recently it has been recognized as an important phenomenon in complementarity Lagrangian systems, where different solutions have been proposed to cope with this issue, some of them inspired by [288]. The peaking phenomenon occurs in trajectory tracking problems when impacts are disturbances [154,156,145,1,289,147,8,290,291,292], and in observer error dynamics. In robot-object systems the occurrence of the jump-mismatch may not be so common (see the item on trajectory tracking in section 6), since it occurs mainly in trajectory tracking when the goal is to compare two different functions or solutions (i.e., the state of the plant and the desired trajectory) at discontinuity times.…”

“…Trajectory tracking control occupies a specific place in the control of nonsmooth systems with state jumps and variable dimension, and can be tackled from different point of views, depending on whether or not the impacts are considered as disturbances [154,156,145,1,289,147,8,290,291,292] (in which case the peaking or mismatch phenomenon is present, see section 4.4), or not [3,318,366,155,157,154,239]. Two main classes emerge: fully-actuated systems [154,156,145,1,289,147,8,290,291,292], and underactuated robot-object systems. Dead-beat controllers can be used to define and stabilize desired trajectories in jugglers, in conjunction with a specific definition of desired trajectories fitted to a juggling system [313, Algorithm 1].…”

Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study

“…Acknowledging the emergence of robots capable of dynamic physical interactions, provided with high-frequency joint torque sensors and high-resolution encoders, the long term vision of our investigation is instead that of impactaware manipulation: we envision robots grabbing and pushing massive objects that have a fast and direct influence on the robot dynamics right after contact is established. In this context, it is fundamental to be able to predict, both from a planning and control point of view, post-impact velocities [16]. This, together with the creation of a publicly available repository of robot-object-environment impact motions, is also the goal of a recently started H2020 EU project 1 .…”