Force modulation of robotic manipulators has been extensively studied for several decades. However, it is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees - a large proportion of them concerning the modulation of interaction forces. This study presents a high-level framework for simultaneous trajectory optimization and force control of the interaction between a manipulator and soft environments, which is prone to external disturbances. Sliding friction and normal contact force are taken into account. The dynamics of the soft contact model and the manipulator are simultaneously incorporated in a trajectory optimizer to generate desired motion and force profiles. A constrained optimization framework based on Alternative Direction Method of Multipliers (ADMM) has been employed to efficiently generate real-time optimal control inputs and high-dimensional state trajectories in a Model Predictive Control fashion. Experimental validation of the model performance is conducted on a soft substrate with known material properties using a Cartesian space force control mode. Results show a comparison of ground truth and real-time model-based contact force and motion tracking for multiple Cartesian motions in the valid range of the friction model. It is shown that a contact model-based motion planner can compensate for frictional forces and motion disturbances and improve the overall motion and force tracking accuracy. The proposed high-level planner has the potential to facilitate the automation of medical tasks involving the manipulation of compliant, delicate, and deformable tissues.

翻译：力调制在机器人操作中已被广泛研究数十年。然而，由于缺乏精确的交互接触建模以及较弱性能保障（其中大部分涉及交互力的调制），该技术尚未在安全关键型应用中得到普遍使用。本研究提出了一种高层框架，用于同时优化机械臂与易受外部干扰的软环境之间交互的轨迹与力控制。该框架考虑了滑动摩擦和法向接触力。软接触模型的动力学与机械臂动力学被同时纳入轨迹优化器，以生成期望的运动与力曲线。基于交替方向乘子法（ADMM）的约束优化框架被采用，以模型预测控制的方式高效生成实时最优控制输入和高维状态轨迹。在具有已知材料特性的软基底上，通过笛卡尔空间力控制模式进行了模型性能的实验验证。结果表明，在摩擦模型的有效范围内，针对多种笛卡尔运动，基于模型的实时接触力与运动追踪与真实值进行了对比。研究表明，基于接触模型运动规划器能够补偿摩擦力和运动扰动，并提高整体运动与力追踪精度。所提出的高层规划器有望推动涉及柔性、精细与可变形组织操作的医疗任务自动化进程。