Impact-Robust Posture Optimization for Aerial Manipulation
Amr Afifi, Ahmad Gazar, Javier Alonso-Mora, Paolo Robuffo Giordano, Antonio Franchi
AI summary
Problem
Standard whole-body controllers ignore instantaneous velocity jumps during impacts, causing dangerous spikes in actuator commands and state variables that can lead to saturation and loss of control.
Approach
The method formulates a configuration-dependent metric that quantifies impact susceptibility and embeds its gradient minimization as a low-priority task within a TSID whole-body controller to iteratively steer the robot into impact-resistant postures.
Key results
- Up to 51% reduction in post-impact configuration spikes for aerial manipulators
- Complete avoidance of actuator saturation during repeated contact tasks
- Up to 45% reduction in post-impact state spikes validated on quadruped and humanoid robots
- Negligible computational overhead via offline gradient computation
Why it matters
Provides a practical, real-time solution for safer and more robust aerial and legged robots performing contact-rich industrial inspection tasks.
Abstract
We present a novel method for optimizing the posture of kinematically redundant torque-controlled robots to improve robustness during impacts. A rigid impact model is used as the basis for a configuration-dependent metric that quantifies the variation between pre- and post-impact velocities. By finding configurations (postures) that minimize the aforementioned metric, spikes in the robot’s state and input commands can be significantly reduced during impacts, improv- ing safety and robustness. The problem of identifying impact- robust postures is posed as a min–max optimization of the aforementioned metric. To overcome the real-time intractability of the problem, we reformulate it as a gradient-based motion task that iteratively guides the robot towards configurations that minimize the proposed metric. This task is embedded within a task-space inverse dynamics (TSID) whole-body controller, enabling seamless integration with other control objectives. The method is applied to a kinematically redundant aerial manipulator performing repeated point contact tasks. We test our method inside a realistic physics simulator and compare it with the nominal TSID. Our method leads to a reduction (up to 51% w.r.t. standard TSID) of post-impact spikes in the robot’s configuration and successfully avoids actuator satura- tion. Moreover, we demonstrate the importance of kinematic redundancy for impact-robustness using additional numerical simulations on a quadruped and a humanoid robot, resulting in up to 45%, reduction of post-impact spikes in the robot’s state w.r.t. nominal TSID.