As access to space and robotic autonomy capabilities move forward, there is simultaneously a growing interest in deploying large, complex space structures to provide new on-orbit capabilities. New space-borne observatories, large orbital outposts, and even futuristic on-orbit manufacturing will be enabled by robotic assembly of space structures using techniques like on-orbit additive manufacturing which can provide flexibility in constructing and even repairing complex hardware. However, the dynamics underlying the robotic assembler during manipulation may operate under inertial uncertainties. Thus, inertial estimation of the robot and the manipulated component system must be considered during structural assembly. The contribution of this work is to address both the motion planning and control for robotic assembly with consideration of the inertial estimation of the combined free-flying robotic assembler and additively manufactured component system. Specifically, the Linear Quadratic Regulator Rapidly-Exploring Randomized Trees (LQR-RRT*) and dynamically feasible path smoothing are used to obtain obstacle-free trajectories for the system. Further, model learning is incorporated explicitly into the planning stages via approximation of the continuous system and accompanying reward of performing safe, objective-oriented motion. Remaining uncertainty can then be dealt with using robust tube model predictive control. By obtaining controlled trajectories that consider both obstacle avoidance and learning of the inertial properties of the free-flyer and manipulated component system, the free-flyer rapidly considers and plans the construction of space structures with enhanced system knowledge. The approach naturally generalizes to repairing, refueling, and re-provisioning space structure components while providing optimal collision-free trajectories under e.g., inertial uncertainty.
翻译:随着进入空间和机器人自主能力的发展,同时对部署大型、复杂的空间结构以提供新的在轨能力的兴趣日益浓厚,新的空间观测站、大型轨道前哨,甚至未来在轨制造,将通过机器人结构的机器人组装,使用诸如在轨添加剂制造等技术,在建造甚至修复复杂硬件方面提供灵活性;然而,操纵过程中机器人装配机背后的动力可能在惯性不确定的情况下运作;因此,在结构组装期间必须考虑对机器人和被操纵组件系统的惯性估计,这项工作的贡献是既解决机器人组装的动作规划和控制,又考虑到自由飞行机器人组装和添加制造组件系统的惯性稳定性估算。具体地说,线性压压式调节器快速开发机的机械化和动态可行的道路平滑动,以便获得系统的无障碍轨迹,同时通过对安全、客观、面向目标的稳定性进行奖励,从而实现安全、面向目标的系统组装件的惯性估算,同时利用稳定的系统稳定、稳定的系统稳定性结构来改进空间结构的稳定性,从而利用稳定的稳定、稳定的稳定性结构来改进空间结构的稳定性,从而改进空间结构的稳定性的稳定性和稳定性的稳定性的稳定性的稳定性的稳定性的稳定性控制。