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arXiv Robotics research summaries for May 09, 2024.
Today's Research Themes (AI-Generated):
• Introduction of Dynamic Deep Factor Graphs (DDFG) to enhance multi-agent reinforcement learning with adaptable value function structures.
• Development of a universal LiDAR calibration method leveraging a coarse-to-fine framework for autonomous systems.
• ASGrasp presents a network for grasping transparent objects using RGB-D active stereo camera, achieving high success rates.
• LOP-UKF combines LiDAR Odometry and the Pacejka tire model for accurate real-time racecar sideslip estimation.
• Proposal of a passive control policy that adapts to obstacles for safe, robust autonomous robot motion.
arXiv Robotics research summaries for May 09, 2024.
Today's Research Themes (AI-Generated):
• Introduction of Dynamic Deep Factor Graphs (DDFG) to enhance multi-agent reinforcement learning with adaptable value function structures.
• Development of a universal LiDAR calibration method leveraging a coarse-to-fine framework for autonomous systems.
• ASGrasp presents a network for grasping transparent objects using RGB-D active stereo camera, achieving high success rates.
• LOP-UKF combines LiDAR Odometry and the Pacejka tire model for accurate real-time racecar sideslip estimation.
• Proposal of a passive control policy that adapts to obstacles for safe, robust autonomous robot motion.