779 citations
- Massachusetts Institute of TechnologyUS13 papers
- Harvard UniversityUS10 papers
- Stanford UniversityUS10 papers
- Technical University of MunichDE9 papers
- Beijing Academy of Artificial IntelligenceCN8 papers
- Monash UniversityAU8 papers
- Shanghai Jiao Tong UniversityCN8 papers
- University of Hong KongHK8 papers
- Harvard University PressUS7 papers
- University of Southern CaliforniaUS7 papers
- Hong Kong University of Science and TechnologyHK6 papers
- Imperial College LondonGB6 papers
8 papers · 1 filter
Robust Adaptive Backstepping Impedance Control of Robots in Unknown Environments
Reza Nazmara, Alap Kshirsagar, Jan Peters +1
This paper presents a Robust Adaptive Backstepping Impedance Control (RABIC) strategy for robots operating in contact-rich and uncertain environments. The proposed control strategy…
Predictive and adaptive maps for long-term visual navigation in changing environments
Lucie Halodova, Eliska Dvorakova, Filip Majer +4
In this paper, we compare different map management techniques for long-term visual navigation in changing environments. In this scenario, the navigation system needs to continuousl…
LA-RCS: LLM-Agent-Based Robot Control System
TaekHyun Park, YoungJun Choi, SeungHoon Shin +1
LA-RCS (LLM-agent-based robot control system) is a sophisticated robot control system designed to autonomously plan, work, and analyze the external environment based on user requir…
Merry-Go-Round: Safe Control of Decentralized Multi-Robot Systems with Deadlock Prevention
Wonjong Lee, Joonyeol Sim, Joonkyung Kim +3
We propose a hybrid approach for decentralized multi-robot navigation that ensures both safety and deadlock prevention. Building on a standard control formulation, we add a lightwe…
CloudTrack: Scalable UAV Tracking with Cloud Semantics
Yannik Blei, Michael Krawez, Nisarga Nilavadi +2
Nowadays, unmanned aerial vehicles (UAVs) are commonly used in search and rescue scenarios to gather information in the search area. The automatic identification of the person sear…
SICNav: Safe and Interactive Crowd Navigation using Model Predictive Control and Bilevel Optimization
Sepehr Samavi, James R. Han, Florian Shkurti +1
Robots need to predict and react to human motions to navigate through a crowd without collisions. Many existing methods decouple prediction from planning, which does not account fo…