The papers submitted by DFKI researchers to IROS 2022 address different issues related to the design and motion control of robotic systems. The paper "Co-optimization of Acrobot Design and Controller for Increased Certifiable Stability" focuses on the question of how the stability of underactuated robots can be improved by simultaneously optimizing the robot design and the control parameters.
A novel methodology for formalizing robot motion using musical dance, demonstrated both in simulation and on the RH5 Manus humanoid robot, is described in the paper "Robot Dance Generation with Music Based Trajectory Optimization". It was also selected as a finalist for the IROS Best Entertainment and Amusement Paper Award.
In the paper " Modular and Hybrid Numerical-Analytical Approach - A Case Study on Improving Computational Efﬁciency for Series-Parallel Hybrid Robots" DFKI researchers introduce, among other things, a case study on the application of a modular and hybrid numerical-analytical approach to the modeling and control of series-parallel hybrid robots.
Entitled "Trajectory Optimization and Following for a Three Degrees of Freedom Overactuated Floating Platform," researchers from various research institutes, including DFKI, address a topic from the field of space robotics. They present a control architecture for trajectory optimization and following for a floating platform in the European Space Agency's ORGL Orbital Robotics and GNC Lab (ORGL).
The accepted papers in detail:
1. Lasse Maywald, Felix Wiebe, Shivesh Kumar, Mahdi Javadi, Frank Kirchner, Co-optimization of Acrobot Design and Controller for Increased Certifiable Stability, In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Unlike fully actuated systems, the control of underactuated robots necessitates the use of passive dynamics to fulfill control objectives. Hence, there is an increased interdependence between design parameters of the robot and the closed loop performance. An acrobot is known to have an unstable upright posture and a linear controller performs better when the inertia of the second link is larger than the first link. This paper proposes a novel approach for co-optimization of robot design and controller parameters for increased certifiable stability obtained with means of region of attraction analysis. In particular, it discusses the co-optimization problem of a gymnastic acrobot robot where the design and the controller are optimized to have a large region of attraction (ROA) taking into account the closed loop dynamics of a non-linear system stabilized by a linear quadratic regulator (LQR) controller. The results are validated by extensive simulation of the acrobot's closed loop dynamics.
Preprint DOI: 10.13140/RG.2.2.36436.07043
2. Melya Boukheddimi, Daniel Harnack, Shivesh Kumar, Rohit Kumar, Shubham Vyas, Octavio Arriaga, Frank Kirchner, Robot Dance Generation with Music Based Trajectory Optimization. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Recently, human-robot interaction is expanding into everyday life, where a specific focus is required on natural interactions. Thus, with musical dancing being a ubiquitous phenomenon in human society, providing robots with the ability to dance has lately generated considerable research interest. In this paper, we present a novel formalization for musical dance as planning and control of optimally timed actions based on beat times and additional music feature extraction. We showcase the use of this formulation in three different variations: Imitation of a predefined choreography, human choreography improvisation, and automated generation of a novel choreography. Our method has been validated on four different musical pieces, both in simulation and on a real robot, using the upper-body humanoid robot RH5 Manus.
Preprint DOI: 10.13140/RG.2.2.29096.03845
3. Rohit Kumar, Shivesh Kumar, Andreas Mueller, Frank Kirchner, Modular and Hybrid Numerical-Analytical Approach - A Case Study on Improving Computational Efﬁciency for Series-Parallel Hybrid Robots. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Modeling closed loop mechanisms is a necessity for the control and simulation of various systems and poses a great challenge to rigid body dynamics algorithms. Solving the forward and inverse dynamics for such systems requires resolution of loop closure constraints which are often solved via numerical procedures. This brings an additional burden to these algorithms as they have to stabilize and control the loop closure errors. In order to avoid this issue, analytical solutions are preferred for commonly studied parallel mechanisms. This paper has two contributions. Firstly, it reports a case study on a modular and hybrid numerical-analytical approach to model and control series-parallel hybrid robots which are subjected to large number of holonomic constraints. The approach exploits modularity in the robot design to combine analytical loop closure for the known submechanisms and numerical loop closure for submechanisms where analytical solutions are not available. This offers an edge over purely numerical approach in terms of computational efficiency. Secondly, an adaptation of the constraint embedding approach in Articulated Body Algorithm (ABA) is presented which yields a recursive algorithm in minimal coordinates for computing the forward dynamics of series-parallel hybrid systems. The proposed modification exploits the Lie group formulations and allows easy implementation of recursive forward dynamics of constrained systems in state-of-the-art multi-body solvers.
Preprint DOI: 10.13140/RG.2.2.10431.38565
4. Anton Bredenbeck, Shubham Vyas, Martin Zwick, Dorit Borrmann, Miguel A. Olivares-Mendez, and Andreas Nuechter. "Trajectory Optimization and Following for a Three Degrees of Freedom Overactuated Floating Platform"
In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Applications of space robotics, such as Active Space Debris Removal (ASDR), require representative testing before launch. A commonly used approach to emulate the microgravity environment in space are air-bearing based platforms on flat-floors, such as the European Space Agency’s Orbital Robotics and GNC Lab (ORGL). This work proposes a control architecture for a floating platform at the ORGL, equipped with eight solenoid-valve-based thrusters and one reaction wheel. The control architecture consists of two main components: a trajectory planner that finds optimal trajectories connecting two states and a trajectory follower that follows any physically feasible trajectory. The controller is first evaluated within an introduced simulation, achieving a 100% success rate at finding and following trajectories to the origin within a Monte-Carlo test. Individual trajectories are also successfully followed by the physical system. In this work, we showcase the ability of the controller to reject disturbances and follow a straight-line trajectory within tens of centimeters.
Dr. rer. nat. Shivesh Kumar
DFKI Robotics Innovation Center
Team Leader Mechanics & Control