  Chemists need to perform many laborious and time-consuming experiments in the
lab to discover and understand the properties of new materials. To support and
accelerate this process, we propose a robot framework for manipulation that
autonomously performs chemistry experiments. Our framework receives high-level
abstract descriptions of chemistry experiments, perceives the lab workspace,
and autonomously plans multi-step actions and motions. The robot interacts with
a wide range of lab equipment and executes the generated plans. A key component
of our method is constrained task and motion planning using PDDLStream solvers.
Preventing collisions and spillage is done by introducing a constrained motion
planner. Our planning framework can conduct different experiments employing
implemented actions and lab tools. We demonstrate the utility of our framework
on pouring skills for various materials and two fundamental chemical
experiments for materials synthesis: solubility and recrystallization.
