A method for autonomous robotic manipulation through exploratory interactions with uncertain environments
- PDF / 4,518,833 Bytes
- 16 Pages / 595.276 x 790.866 pts Page_size
- 48 Downloads / 200 Views
A method for autonomous robotic manipulation through exploratory interactions with uncertain environments Pietro Balatti1,2
· Dimitrios Kanoulas3 · Nikos Tsagarakis4 · Arash Ajoudani1
Received: 17 June 2019 / Accepted: 14 July 2020 © The Author(s) 2020
Abstract Expanding robot autonomy can deliver functional flexibility and enable fast deployment of robots in challenging and unstructured environments. In this direction, significant advances have been recently made in visual-perception driven autonomy, which is mainly due to the availability of rich sensory data-sets. However, current robots’ physical interaction autonomy levels still remain at a basic level. Towards providing a systematic approach to this problem, this paper presents a new context-aware and adaptive method that allows a robotic platform to interact with unknown environments. In particular, a multi-axes selftuning impedance controller is introduced to regulate quasi-static parameters of the robot based on previous experience in interacting with similar environments and the real-time sensory data. The proposed method is also capable of differentiating internal and external disruptions, and responding to them accordingly and appropriately. An agricultural experiment with different deformable material is presented to validate robot interaction autonomy improvements, and the capability of the proposed methodology in detecting and responding to unexpected events (e.g., faults). Keywords Robotic manipulation · Interaction autonomy · Impedance control · Adaptive control
1 Introduction To respond to the rapidly increasing demand for high levels of flexibility in manufacturing and service applications, recent Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10514-020-09933-w) contains supplementary material, which is available to authorized users.
B
Pietro Balatti [email protected] Dimitrios Kanoulas [email protected] Nikos Tsagarakis [email protected] Arash Ajoudani [email protected]
1
HRI Laboratory, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genoa, Italy
2
Department of Information Engineering, University of Pisa, Pisa, Italy
3
Department of Computer Science, University College London, Gower Street, WC1E 6BT London, UK
4
HHCM Laboratory, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genoa, Italy
research has focused on endowing robots with the ability to react and adapt to their environments. From the one hand, robotic systems based on torque sensing and actuation or variable impedance mechanisms have been developed to make them compliant to their surroundings (Albu-Schaffer et al. 2003; Tsagarakis et al. 2016). On the software level instead, a great deal of attention has been devoted to the perception autonomy of the robots, to capture the effects of appearance and context (Kotseruba et al. 2016; Harbers et al. 2017). Although these two directions have seen significant advancements over the past decade, the bridging action, i.e., associating perception to int
Data Loading...
