Proactive Model Predictive Control with Multi-Modal Human Motion Prediction in Cluttered Dynamic Environments

Heuer, Lukas,1992-Örebro universitet,Institutionen för naturvetenskap och teknik,AASS (författare)

For robots navigating in dynamic environments, exploiting and understanding uncertain human motion prediction is key to generate efficient, safe and legible actions. The robot may perform poorly and cause hindrances if it does not reason over possible, multi-modal future social interactions. With the goal of enhancing autonomous navigation in cluttered environments, we propose a novel formulation for nonlinear model predictive control including multi-modal predictions of human motion. As a result, our approach leads to less conservative, smooth and intuitive human-aware navigation with reduced risk of collisions, and shows a good balance between task efficiency, collision avoidance and human comfort. To show its effectiveness, we compare our approach against the state of the art in crowded simulated environments, and with real-world human motion data from the THOR dataset. This comparison shows that we are able to improve task efficiency, keep a larger distance to humans and significantly reduce the collision time, when navigating in cluttered dynamic environ-ments. Furthermore, the method is shown to work robustly with different state-of-the-art human motion predictors.

Palmieri, LuigiRobert Bosch GmbH, Corporate Research, Stuttgart, Germany (författare)
Rudenko, Andrey,1991-Robert Bosch GmbH, Corporate Research, Stuttgart, Germany (författare)
Mannucci, AnnaRobert Bosch GmbH, Corporate Research, Stuttgart, Germany (författare)
Magnusson, Martin,Docent,1977-Örebro universitet,Institutionen för naturvetenskap och teknik,AASS(Swepub:oru)mnmn (författare)
Arras, Kai ORobert Bosch GmbH, Corporate Research, Stuttgart, Germany (författare)
Örebro universitetInstitutionen för naturvetenskap och teknik (creator_code:org_t)

Ingår i:2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 01-05 October 2023, Detroit, MI, USA: IEEE, s. 229-23697816654919149781665491907

Av författaren/redakt...: Heuer, Lukas, 19 ...; Palmieri, Luigi; Rudenko, Andrey, ...; Mannucci, Anna; Magnusson, Marti ...; Arras, Kai O

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