Impact-Aware Task-Space Quadratic-Programming Control

Generating on-purpose impacts with rigid robots is challenging as they may lead to severe hardware failures due to abrupt changes in the velocities and torques. Without dedicated hardware and controllers, robots typically operate at a near-zero velocity in the vicinity of contacts. We assume knowing how much of impact the hardware can absorb and focus solely on the controller aspects. The novelty of our approach is twofold: (i) it uses the task-space inverse dynamics formalism that we extend by seamlessly integrating impact tasks; (ii) it does not require separate models with switches or a reset map to operate the robot undergoing impact tasks. Our main idea lies in integrating post-impact states prediction and impact-aware inequality constraints as part of our existing general-purpose whole-body controller. To achieve such prediction, we formulate task-space impacts and its spreading along the kinematic tree of a floating-base robot with subsequent joint velocity and torque jumps. As a result, the feasible solution set accounts for various constraints due to expected impacts. In a multi-contact situation of under-actuated legged robots subject to multiple impacts, we also enforce standing stability margins. By design, our controller does not require precise knowledge of impact location and timing. We assessed our formalism with the humanoid robot HRP-4, generating maximum contact velocities, neither breaking established contacts nor damaging the hardware

A Projected Inverse Dynamics Approach for Multi-arm Cartesian Impedance Control

Lin H-C, Smith J, Kouhkiloui Babarahmati K, Dehio N, Mistry M. A Projected Inverse Dynamics Approach for Multi-arm Cartesian Impedance Control. In: IEEE/RSJ Int. Conf. on Robotics and Automation. 2018.We propose a model-based control framework for multi-arm manipulation of a rigid object subject to external disturbances. The control framework, based on projected inverse dynamics, decomposes the control law into constrained and unconstrained subspaces. Unconstrained components accomplish the motion task with a desired 6-DOF Cartesian impedance behaviour against external disturbances. Meanwhile, the constrained component enforces contact and friction constraints by optimising for contact forces within the constrained subspace. External disturbances are explicitly compensated for without using force/torque sensors at the contact points. The approach is evaluated on a dual-arm platform manipulating a rigid object while coping with unknown object dynamics and human interaction

Modeling and Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics during Grasping

Dehio N, Smith J, Wigand DL, et al. Modeling & Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics during Grasping. In: IEEE/RSJ Int. Conf. on Robotics and Automation. 2018

Domain-Specific Language Modularization Scheme Applied to a Multi-Arm Robotics Use-Case

Wigand DL, Nordmann A, Dehio N, Mistry M, Wrede S. Domain-Specific Language Modularization Scheme Applied to a Multi-Arm Robotics Use-Case. Journal of Software Engineering for Robotics. 2017;8(1):45-64

Prioritized Multi-Objective Robot Control

Dehio N. Prioritized Multi-Objective Robot Control. Braunschweig: Technical University of Braunschweig, Germany; 2018

A Comparison of Null-space Projection and Mixture of Torque Controllers for Motion Generation

Dehio N, Steil JJ. A Comparison of Null-space Projection and Mixture of Torque Controllers for Motion Generation. In: Proc. 9th Int. Workshop on Human-Friendly Robotics. 2016

Dynamically-consistent Generalized Hierarchical Control

Dehio N, Steil JJ. Dynamically-consistent Generalized Hierarchical Control. In: IEEE/RSJ Int. Conf. on Robotics and Automation. 2019

Predicting Impact-Induced Joint Velocity Jumps on Kinematic-Controlled Manipulator

In order to enable on-purpose robotic impact tasks, predicting joint-velocity jumps is essential to enforce controller feasibility and hardware integrity. We observe a considerable prediction error of a commonly-used approach in robotics compared against 250 benchmark experiments with the Panda manipulator. We reduce the average prediction error by 81.98% as follows: First, we focus on task-space equations without inverting the ill-conditioned joint-space inertia matrix. Second, before the impact event, we compute the equivalent inertial properties of the end-effector tip considering that a high-gains (stiff) kinematic-controlled manipulator behaves like a composite-rigid body

Model-Based Specification of Control Architectures for Compliant Interaction with the Environment

Wigand DL, Dehio N, Wrede S. Model-Based Specification of Control Architectures for Compliant Interaction with the Environment. In: Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020). 2020

Continuous Task-Priority Rearrangement during Motion Execution with a Mixture of Torque Controllers

Dehio N, Reinhart F, Steil JJ. Continuous Task-Priority Rearrangement during Motion Execution with a Mixture of Torque Controllers. In: 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids). IEEE; 2016: 264-270