ORGANA is an assistive robotic system designed to automate diverse chemistry experiments using decision-making and perception tools. It enables seamless interaction between chemists and lab devices, allowing chemists to control robots and lab equipment while making decisions in real-time. ORGANA uses Large Language Models (LLMs) to interact with chemists, derive experiment goals, handle disambiguation, and provide experiment logs. It plans and executes complex tasks with visual feedback, while supporting scheduling and parallel task execution. ORGANA reduces frustration and physical demand by over 50%, with users saving an average of 80.3% of their time when using it. ORGANA is a suite of algorithmic tools for robot interaction, perception, and decision making, and is a continuation of our previous work CLAIRify. ORGANA uses LLMs to interact with chemists, identify experiment goals, and plan robot experiments. It also offers feedback to chemists by analyzing experiment outputs. ORGANA allows for intuitive communication in natural language with chemists, utilizing either written or speech modalities, thereby reducing human effort and keeping chemists informed of high-level decisions throughout the experiment. ORGANA provides chemists with a summary of experiments, their results, and analysis in the form of a report. This approach provides chemists with comprehensive feedback and enables timely user intervention when necessary. ORGANA also has 3D visual perception capabilities, which enables the manipulation of objects as well as monitoring the progress of chemistry experiments. This allows ORGANA to make informed decisions on how robots will interact with lab equipment and when to proceed to the next step of a long experiment. The combination of autonomous decision-making and high-level human involvement when necessary contributes to the overall robustness of the system, while reducing the amount of manual involvement in the experiment. Additionally, ORGANA is oriented towards modularity, in terms of both hardware and functional components, empowering scientists to adopt them for various purposes and a diverse set of experiments and hardware setups. ORGANA also supports the parallel execution of chemistry experiments, reducing the overall experiment makespan and enhancing efficiency. ORGANA receives commands from chemists in audio or text format, translates them using an LLM-based reasoning architecture into an experiment task description, and then maps these instructions to the robot's goals. Additionally, it grounds perceived objects in the scene through user interaction. ORGANA improves efficiency by simultaneously solving task and motion planning (TAMP) and scheduling problems, enabling parallel execution of tasks. Moreover, ORGANA provides feedback to users by offering a comprehensive report and analysis and notifying them in case of unexpected results during the experiment. ORGANA is used to execute four widely-used, fundamental chemistry experiments: solubility screening, recrystallization, pH experimentation, and electrochemistry characterization. Solubility screening is an example of using perceptual feedback to make decisions on when to stop the experiment. ORGANA is utilized to identify the electroORGANA is an assistive robotic system designed to automate diverse chemistry experiments using decision-making and perception tools. It enables seamless interaction between chemists and lab devices, allowing chemists to control robots and lab equipment while making decisions in real-time. ORGANA uses Large Language Models (LLMs) to interact with chemists, derive experiment goals, handle disambiguation, and provide experiment logs. It plans and executes complex tasks with visual feedback, while supporting scheduling and parallel task execution. ORGANA reduces frustration and physical demand by over 50%, with users saving an average of 80.3% of their time when using it. ORGANA is a suite of algorithmic tools for robot interaction, perception, and decision making, and is a continuation of our previous work CLAIRify. ORGANA uses LLMs to interact with chemists, identify experiment goals, and plan robot experiments. It also offers feedback to chemists by analyzing experiment outputs. ORGANA allows for intuitive communication in natural language with chemists, utilizing either written or speech modalities, thereby reducing human effort and keeping chemists informed of high-level decisions throughout the experiment. ORGANA provides chemists with a summary of experiments, their results, and analysis in the form of a report. This approach provides chemists with comprehensive feedback and enables timely user intervention when necessary. ORGANA also has 3D visual perception capabilities, which enables the manipulation of objects as well as monitoring the progress of chemistry experiments. This allows ORGANA to make informed decisions on how robots will interact with lab equipment and when to proceed to the next step of a long experiment. The combination of autonomous decision-making and high-level human involvement when necessary contributes to the overall robustness of the system, while reducing the amount of manual involvement in the experiment. Additionally, ORGANA is oriented towards modularity, in terms of both hardware and functional components, empowering scientists to adopt them for various purposes and a diverse set of experiments and hardware setups. ORGANA also supports the parallel execution of chemistry experiments, reducing the overall experiment makespan and enhancing efficiency. ORGANA receives commands from chemists in audio or text format, translates them using an LLM-based reasoning architecture into an experiment task description, and then maps these instructions to the robot's goals. Additionally, it grounds perceived objects in the scene through user interaction. ORGANA improves efficiency by simultaneously solving task and motion planning (TAMP) and scheduling problems, enabling parallel execution of tasks. Moreover, ORGANA provides feedback to users by offering a comprehensive report and analysis and notifying them in case of unexpected results during the experiment. ORGANA is used to execute four widely-used, fundamental chemistry experiments: solubility screening, recrystallization, pH experimentation, and electrochemistry characterization. Solubility screening is an example of using perceptual feedback to make decisions on when to stop the experiment. ORGANA is utilized to identify the electro