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Robots learn to throw objects safely in cluttered environments

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new method for robotic throwing that can safely navigate cluttered environments. This approach uses a potential field state representation to guide reinforcement learning policies, allowing robots to generalize across various obstacle configurations. The method, which was initialized with kinesthetic demonstrations and optimized using SAC, DDPG, and TD3 algorithms, achieved up to 90% success in real-world experiments with unseen objects and cluttered scenes. AI

IMPACT Enables robots to perform precise object placement in complex, real-world scenarios.

RANK_REASON This is a research paper detailing a new method for robotic throwing.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Robots learn to throw objects safely in cluttered environments

COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Mohammadreza Kasaei, Klemen Voncina, Hamidreza Kasaei ·

    Learning to Throw Objects Safely in Multi-Obstacle Environments

    arXiv:2607.06388v1 Announce Type: cross Abstract: Robotic throwing enables fast and efficient object placement beyond the robot's immediate workspace, but reliable throwing in cluttered environments remains underexplored. Existing approaches, such as TossingBot, learn throwing st…

  2. arXiv cs.LG TIER_1 English(EN) · Hamidreza Kasaei ·

    Learning to Throw Objects Safely in Multi-Obstacle Environments

    Robotic throwing enables fast and efficient object placement beyond the robot's immediate workspace, but reliable throwing in cluttered environments remains underexplored. Existing approaches, such as TossingBot, learn throwing strategies from visual input but assume obstacle-fre…

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