KiloBot: A Programming Language for Deploying Perception-Guided Industrial Manipulators at Scale

Kavli Affiliate: Wei Gao

| First 5 Authors: Wei Gao, Jingqiang Wang, Xinv Zhu, Jun Zhong, Yue Shen

| Summary:

We would like industrial robots to handle unstructured environments with
cameras and perception pipelines. In contrast to traditional industrial robots
that replay offline-crafted trajectories, online behavior planning is required
for these perception-guided industrial applications. Aside from perception and
planning algorithms, deploying perception-guided manipulators also requires
substantial effort in integration. One approach is writing scripts in a
traditional language (such as Python) to construct the planning problem and
perform integration with other algorithmic modules & external devices. While
scripting in Python is feasible for a handful of robots and applications,
deploying perception-guided manipulation at scale (e.g., more than 10000 robot
workstations in over 2000 customer sites) becomes intractable. To resolve this
challenge, we propose a Domain-Specific Language (DSL) for perception-guided
manipulation applications. To scale up the deployment,our DSL provides: 1) an
easily accessible interface to construct & solve a sub-class of Task and Motion
Planning (TAMP) problems that are important in practical applications; and 2) a
mechanism to implement flexible control flow to perform integration and address
customized requirements of distinct industrial application. Combined with an
intuitive graphical programming frontend, our DSL is mainly used by machine
operators without coding experience in traditional programming languages.
Within hours of training, operators are capable of orchestrating interesting
sophisticated manipulation behaviors with our DSL. Extensive practical
deployments demonstrate the efficacy of our method.

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