A Passivity-based Nonlinear Admittance Control with Application to Powered Upper-limb Control under Unknown Environmental Interactions

This paper presents an admittance controller based on the passivity theory for a powered upper-limb exoskeleton robot which is governed by the nonlinear equation of motion. Passivity allows us to include a human operator and environmental interaction in the control loop. The robot interacts with the human operator via F/T sensor and interacts with the environment mainly via end-effectors. Although the environmental interaction cannot be detected by any sensors (hence unknown), passivity allows us to have natural interaction. An analysis shows that the behavior of the actual system mimics that of a nominal model as the control gain goes to infinity, which implies that the proposed approach is an admittance controller. However, because the control gain cannot grow infinitely in practice, the performance limitation according to the achievable control gain is also analyzed. The result of this analysis indicates that the performance in the sense of infinite norm increases linearly with the control gain. In the experiments, the proposed properties were verified using 1 degree-of-freedom testbench, and an actual powered upper-limb exoskeleton was used to lift and maneuver the unknown payload.Comment: Accepted in IEEE/ASME Transactions on Mechatronics (T-MECH

Proprioceptive Sensor-Based Simultaneous Multi-Contact Point Localization and Force Identification for Robotic Arms

In this paper, we propose an algorithm that estimates contact point and force simultaneously. We consider a collaborative robot equipped with proprioceptive sensors, in particular, joint torque sensors (JTSs) and a base force/torque (F/T) sensor. The proposed method has the following advantages. First, fast computation is achieved by proper preprocessing of robot meshes. Second, multi-contact can be identified with the aid of the base F/T sensor, while this is challenging when the robot is equipped with only JTSs. The proposed method is a modification of the standard particle filter to cope with mesh preprocessing and with available sensor data. In simulation validation, for a 7 degree-of-freedom robot, the algorithm runs at 2200Hz with 99.96% success rate for the single-contact case. In terms of the run-time, the proposed method was >=3.5X faster compared to the existing methods. Dual and triple contacts are also reported in the manuscript.Comment: 2023 International Conference on Robotics and Automation (ICRA

Design of a momentum-based disturbance observer for rigid and flexible joint robots

Disturbance observer (DOB) is widely used in many practical applications due to its simple structure and high performance. However, the DOB cannot be directly applied to the robotic systems because of the nonlinearities/couplings in the inertia matrix (by means of coupling, we mean off-diagonal terms of the inertia matrix). This paper proposes a momentum-based DOB for general rigid joint robotic systems. By introducing the generalized momentum, it is possible to utilize full nonlinearities and couplings of the inertia matrix in the DOB design. Moreover, the momentum-based DOB design for the rigid joint robots can be easily extended to the flexible joint robot applications by applying it to the link-side dynamics and motor-side dynamics, respectively. As a result, we can estimate the external torque acting on the link-side and can compensate the disturbance occurring in the motor-side at the same time. Uniformly ultimated boundedness of the closed-loop dynamics can be shown through the Lyapunov-like approaches. The proposed scheme is verified using the numerical simulations.X1134sciescopu