A target-approachable force-guided control with adaptive accommodation for complex assembly

Abstract

In this paper, a target approachable force-guided control with adaptive accommodation for complex assembly is presented. Complex assembly (CA) is defined as a task which deals with complex shaped parts including concavity, or whose environment is so complex that unexpected contacts occur frequently during insertion. CA tasks are encountered frequently in the field of manufacturing automation and various robot applications. To make CA successful, both the bounded wrench condition and the target approachability condition should be satisfied simultaneously during insertion. The bounded wrench condition can be satisfied by properly designing accommodation parameters, which depends on the tolerable stiffness for an assembly task, not to exceed the prescribed contact wrench. On the other hand. the target approachability condition can be satisfied by determining an admissible twist minimizing the deviation between the current and target twist. By applying convex optimization techniques, an optimum target approaching twist can be determined at each instantaneous contact state as a global minimum solution. Incorporated with an admissible perturbation method, a new CA algorithm using only the sensed resultant wrench and the target twist is developed without motion planning or contact analysis (which requires the geometry of the part and the environment). To verify the feasibility of the new assembly algorithm, a wench sensor model based on a minimum distance algorithm has been developed and used to estimate contact wrenches in graphic assembly simulation. Finally, a VME bus-based real-time control system is built for experiments on various CA tasks. The T-insertion task as a planar CA, and the double-peg assembly task as a spatial C A, were successfully executed by implementing the new force-guided control with adaptive accommodation.

Model predictive disturbance rejection during cooperative mobile robot assembly tasks

“…The methods developed to date generally rely on assumptions that include: flat and hard terrain; accurate knowledge of the environment; little or no task uncertainty; and sufficient sensing capability. Additionally, researchers have developed several approaches to the single robot object insertion problem including motion in direction of least resistance, perturbation methods, petri-nets and event-based approaches, and remote compliance center modeling for contact state identification (Giraud and Sidobre, 1992;Hirai and Iwata, 1992;Kang et al, 1998;Kitagaki et al, 1993;Kittipongpattana and Laowattana, 1998;Lee and Asada, 1999;McCarragher and Asada, 1993;Shimokura and Muto, 1996;Xiao and Liu, 1998).…”

Least squares tracking on the Euclidean group

“…Xiao et al [6] of hybrid position-force control in uncalibrated environments. Kang [1] formulates the complex assembly problem as a screw-based local quadratic parameter optimization problem subject to linear inequality constraints, and finds a closed-form solution. More closer in spirit to our work is that of Walsh et al [4], who investigate a class of unconstrained optimal control problems on matrix Lie groups, and Bullo and Murray [7], who provide a geometric formulation of PID control on the Euclidean group.…”