Where to Look Next: Learning Viewpoint Recommendations for Informative Trajectory Planning

  Рет қаралды 508

Autonomous Multi-Robots Lab Delft

Autonomous Multi-Robots Lab Delft

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Planning among decision-making agents
20:03
Autonomous Multi-Robots Lab Delft
Рет қаралды 843
Topology-Driven Parallel Trajectory Optimization in Dynamic Environments
3:57
Autonomous Multi-Robots Lab Delft
Рет қаралды 419
How Strong Is Tape?
00:24
Stokes Twins
Рет қаралды 96 МЛН
Chain Game Strong ⛓️
00:21
Anwar Jibawi
Рет қаралды 41 МЛН
Distributed Nonlinear Trajectory Optimization for Multi-Robot Motion Planning
5:02
Autonomous Multi-Robots Lab Delft
Рет қаралды 475
Learning Interaction aware Guidance Policies for Motion Planning in Dense Traffic Scenarios
4:34
Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning
2:57
Decentralized Probabilistic Multi-Robot Collision Avoidance
2:13
Autonomous Multi-Robots Lab Delft
Рет қаралды 931
Particle-based Instance-aware Semantic Occupancy Mapping in Dynamic Environments
3:40
Autonomous Multi-Robots Lab Delft
Рет қаралды 60
Demonstrating Adaptive Mobile Manipulation in Retail Environments
5:40
Autonomous Multi-Robots Lab Delft
Рет қаралды 84
Curvature Aware Motion Planning with Closed-Loop Rapidly-exploring Random Trees
1:08
Autonomous Multi-Robots Lab Delft
Рет қаралды 412
How Strong Is Tape?
00:24
Stokes Twins
Рет қаралды 96 МЛН