Robust Adaptive Backstepping Impedance Control of Robots in Unknown Environments
Authors: Reza Nazmara, Alap Kshirsagar, Jan Peters, A. Pedro Aguiar
Organizations: Research Center for Systems and Technologies (SYSTEC), ARISE, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal. · Intelligent Autonomous Systems Lab, Department of Computer Science, TU Darmstadt, Germany.
This paper presents a Robust Adaptive Backstepping Impedance Control (RABIC) strategy for robots operating in contact-rich and uncertain environments. The proposed control strategy considers the complete coupled dynamics of the system and explicitly accounts for key sources of uncertainty, including external disturbances and unmodeled dynamics, while not requiring the robot's dynamic parameters in implementation. We propose a backstepping-based adaptive impedance control scheme for the inner loop to track the reference impedance model. To handle uncertainties, we employ a Taylor series-based estimator for system dynamics and an adaptive estimator for determining the upper bound of external forces. Stability analysis demonstrates the semi-global practical finite-time stability of the overall system. To demonstrate the effectiveness of the proposed method, a simulated mobile manipulator scenario and experimental evaluations on a real Franka Emika Panda robot were conducted. The proposed approach exhibits safer performance compared to PD control while ensuring trajectory tracking and force monitoring. Overall, the RABIC framework provides a solid basis for future research on adaptive and learning-based impedance control for coupled mobile and fixed serially linked manipulators.
Figures & tables
Figure 1: Overall block diagram of the proposed control strategy. A model reference impedance defines the desired inner-loop behavior. A Taylor series–based estimator and a force upper bound estimator in the backstepping control handle uncertainties and manage unwanted collisions in the WCMM’s and fixed-base manipulators’ joint space.
Figure 2: (A.1)–(A.3): Snapshots and force profiles for collisions under PD control with a red box ( mr=2.5,5,20kg ). The robot, unaware of contact, follows its trajectory, causing impacts that knock over or push the box. The contact force increases with heavier boxes, highlighting the risks of damage and instability without interaction-aware control. For lighter boxes, PD control pushes the box until it falls, while the 20 kg box moves without knocking over.
Figure 3: (B.1)–(B.3): Snapshots and force profiles for three collision scenarios under the proposed adaptive impedance control, where the robot impacts a red box ( mr=2.5,5,20kg ). Trajectory adaptation in response to collisions rapidly attenuates contact forces. For lighter boxes, the system behaves similarly to a PD controller, while for heavier boxes, it limits force growth by relaxing trajectory tracking to ensure safety and stability.
Figure 4: Joint control efforts τr under the proposed robust adaptive impedance control for Scenario B.3.
Figure 5: The real FR3 Robot during a collision with a box.
Figure 6: (C)–(D): Comparison of Scenario C (PD control) and Scenario D (proposed impedance control) for the real FR3 Robot. Columns show collision joint torque, control effort, and inner loop tracking error.
The authors are with the Faculty of Mechanical Engineering, Sungkyunkwan University, Suwon 2066, South Korea · The authors are with the Faculty of Intelligent Robotics, Sungkyunkwan University, Suwon 2066, South Korea