Control techniques like MPC can realize contact-rich manipulation which exploits dynamic information, maintaining friction limits and safety constraints. However, contact geometry and dynamics are required to be known. This information is often extracted from CAD, limiting scalability and the ability to handle tasks with varying geometry. To reduce the need for a priori models, we propose a framework for estimating contact models online based on torque and position measurements. To do this, compliant contact models are used, connected in parallel to model multi-point contact and constraints such as a hinge. They are parameterized to be differentiable with respect to all of their parameters (rest position, stiffness, contact location), allowing the coupled robot/environment dynamics to be linearized or efficiently used in gradient-based optimization. These models are then applied for: offline gradient-based parameter fitting, online estimation via an extended Kalman filter, and online gradient-based MPC. The proposed approach is validated on two robots, showing the efficacy of sensorless contact estimation and the effects of online estimation on MPC performance. Video results can be seen at https://youtu.be/CuCTcmn3H-o.

Industrial robots have increased payload, repeatability, and reach compared to collaborative robots, however, they have a fixed position controller and low intrinsic admittance. This makes realizing safe contact challenging due to large contact force overshoots in contact transitions and contact instability when the environment and robot dynamics are coupled. To improve safe contact on industrial robots, we propose an admittance controller with inverse model compensation, designed and implemented outside the position controller. By including both the inner loop and outer loop dynamics in its design, the proposed method achieves expanded admittance in terms of increasing both gain and cutoff frequency of the desired admittance. Results from theoretical analyses and experiments on a commercial industrial robot show that the proposed method improves rendering of the desired admittance while maintaining contact stability. We further validate this by conducting actual assembly tasks of plug insertion with fine positioning, switch insertion onto the rail, and colliding the robot end effector with random objects and surfaces, as seen at https://youtu.be/8XfkdHEdWDs.

Admittance and impedance controllers are often purely feedforward, using measured external force or motion, respectively, to generate a reference for an inner-loop controller. In this case, the range of dynamics which can be rendered is limited by the inner-loop, which causes, e.g. contact stability issues for low admittance industrial robots in stiff contact. When both position and force are measured, feedback control can be added to more flexibly reshape the rendered dynamics. This paper uses velocity feedback to increase the admittance of motion-controlled industrial robots in force control applications. This allows an industrial robot with a lower intrinsic admittance, which may be needed for payload, speed, or accuracy, to realize a higher admittance by control, allowing lighter manual guidance and safer contact. This is achieved by a modified disturbance observer, where an inverse dynamic model estimates external forces and amplifies them with positive feedback. This approach is compared with using positive velocity feedback with a shaping filter. Here, velocity reference calculated by the virtual admittance model is modified by the DOB (Dist-Add) or the positive velocity feedback (Vel-Add). When combined with an outer-loop admittance controller, these methods can render a higher admittance while maintaining contact stability compared to standard feedforward admittance control.

Safe physical interaction using admittance control on an industrial robot with inner-loop motion control remains challenging. This is partly due to the low intrinsic admittance and stability issues from inner-loop motion control limitations (e.g. bandwidth). To increase the admittance at an interaction point with the user/environment, this paper proposes a robust admittance control architecture. A disturbance observer (DOB) is used to improve effective inner-loop motion control, suppressing the effects of velocity disturbances. The DOB uses the robot's closed-loop task space velocity control as the nominal model, compensating disturbances between the commanded robot velocity and realized robot velocity output. An admittance controller uses measured force to generate robot velocity commands. Detailed analyses are carried out to theoretically evaluate the proposed control system. Experiments conducted on a COMAU RACER-7-1.4 industrial robot verify the effectiveness of the proposed admittance control scheme and stability in environmental contact. Moreover, the proposed method is simple to implement on the existing robot system.

This paper presents a comprehensive comparative study of the multisensor-based force observers for accurate force control. A force controlled system which contains a force sensor for measuring force transmitted to the load by the motor and an encoder for measuring motor position is considered as the general multisensor-based motion system in this study. Even though these multisensor-based motion systems are emerging as potential motion systems as the demands for collaborative robots increase, there has been few studies that investigate their advantages and limitations. to address this issue, three types of observer-based force controllers that utilize the multisensors are designed and implemented. These controllers exploit the availability of force sensor, motor encoder, and motor torque information from the multisensor-based motion system to estimate accurate force which is later utilized to close the feedback loop. Mathematical and quantitative analyses are conducted to compare performances of the proposed observer-based force control and through this, their advantages and limitations are pointed out. Finally, simulation and an experimental case study with an actual robot are conducted to validate the force tracking performance of the designed force control systems.

Instability which occurs when the robot’s end effector contacts a very stiff environment is a challenge in designing control systems for safe physical interaction and cooperation of robots with environment. One of the reasons for the instability is force disturbances caused by the mechanical factors of the robot system. To this effect, this paper presents the design, analysis, and implementation of a robust impedance controller for a force servo system. To suppress the force disturbances, a force disturbance observer (FDOB) is implemented in the impedance-controlled system. For comparison purposes, impedance control system when the FDOB is not implemented is also designed and analyzed. Further, using the passivity approach, coupled stability conditions of the designed impedance control systems are derived and analyzed to assess the effect of FDOB on passivity and overall control performance. Simulations and experiments are conducted to evaluate performance of the designed impedance control systems and it is found that the FDOB-based control system shows superior performance by improving contact stability compared to direct force sensor feedback control system.

Low frequency dynamic force offsets and measurement noises make utilization of force sensor signal a difficult task, especially, the direct feedback of force measurements in force control systems. To solve these force sensor problems, a novel Kalman filter-based force observer that automatically estimates and eliminates force sensor offsets and attenuates measurement noises is developed in this paper. A dynamic model of force sensing system is derived taking into consideration the dynamic interaction among the motor, the load, and the force sensor between them, as well as the measurement equations. The state-space representation of dynamic force offsets is formulated and augmented to the system dynamic equations from which a state-space Kalman filter is designed. The properties of the designed Kalman filter are further theoretically analyzed in the transfer function form. To verify its effectiveness, experiments are carried out where performance comparison is made to that of a conventional Kalman filter. The proposed observer is found to perform better than the conventional one. Moreover, the transfer function form exhibits a simple structure which makes it simple to implement.