Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study (1404.3785v1)

Abstract: Developing robot agnostic software frameworks involves synthesizing the disparate fields of robotic theory and software engineering while simultaneously accounting for a large variability in hardware designs and control paradigms. As the capabilities of robotic software frameworks increase, the setup difficulty and learning curve for new users also increase. If the entry barriers for configuring and using the software on robots is too high, even the most powerful of frameworks are useless. A growing need exists in robotic software engineering to aid users in getting started with, and customizing, the software framework as necessary for particular robotic applications. In this paper a case study is presented for the best practices found for lowering the barrier of entry in the MoveIt! framework, an open-source tool for mobile manipulation in ROS, that allows users to 1) quickly get basic motion planning functionality with minimal initial setup, 2) automate its configuration and optimization, and 3) easily customize its components. A graphical interface that assists the user in configuring MoveIt! is the cornerstone of our approach, coupled with the use of an existing standardized robot model for input, automatically generated robot-specific configuration files, and a plugin-based architecture for extensibility. These best practices are summarized into a set of barrier to entry design principles applicable to other robotic software. The approaches for lowering the entry barrier are evaluated by usage statistics, a user survey, and compared against our design objectives for their effectiveness to users.

• The paper identifies key design principles—immediacy, transparency, and extensibility—that lower entry barriers for complex robotic software.
• It introduces the MoveIt! Setup Assistant and accompanying visualization and benchmarking tools that automate configuration and performance tuning.
• Empirical results reveal increased adoption and positive user feedback, underscoring enhanced usability and accessibility in robotic applications.

Reducing the Barrier to Entry of Complex Robotic Software: A MoveIt! Case Study

The paper "Reducing the Barrier to Entry of Complex Robotic Software: A MoveIt! Case Study" presents a thorough investigation into lowering the barriers associated with initiating the use of complex robotic software. Notably using the MoveIt! framework as an example, the authors explore various methodologies to simplify the process for new users, including academic researchers, engineers, students, and hobbyists with a general aptitude for robotics software.

Background and Motivation

Robotics software frameworks are inherently complex, blending robotics theory with software engineering while accommodating diverse hardware designs. As these frameworks evolve, they inevitably become more challenging to set up and comprehend for novice users. Hence, the paper posits that despite the sophistication of a robotic software framework, it remains ineffectual if it presents insurmountable barriers for end-users during setup and customization processes. Consequently, this paper explores strategies for reducing these barriers, leveraging MoveIt!, an open-source tool for robotic manipulation in ROS, allowing users to streamline its configuration and optimization and customize its components effortlessly.

Key Contributions and Methodologies

The paper identifies several essential principles for lowering the entry barriers to robotic software which include immediacy, transparency, intuitiveness, reconfigurability, extensibility, and thorough documentation. These principles guide the development of the MoveIt! software enhancing its accessibility and usability:

1. Immediate Implementation: Enables new users to quickly achieve fundamental tasks using the software, akin to a "Hello World" for robotics.
2. MoveIt! Setup Assistant (SA): A central innovation allowing automated configuration of necessary setup files. The SA simplifies the orchestration of the MoveIt! framework with a novel robot by facilitating robot model file creation, collision matrix generation, and semantic representation in SRDF.
3. Visualization and Benchmarking Tools: MoveIt!'s visualization GUI supports learning and experimentation while its benchmarking tools enhance algorithmic performance. The paper highlights the use of automated runtime tuning and parameter sweeping to maximize efficiency and reduce the need for expert manual input.
4. Automated Configuration and Extensibility: Emphasizes a plugin-based architecture conducive to the integration of additional or custom motion planning components. In this way, MoveIt! accommodates comprehensive extensibility by allowing developers to substitute default components without major rewrites.

Empirical Results

The authors quantify the framework's impact via adoption rates, contribution levels, survey insights, and anecdotal user experiences. Significantly, the MoveIt! framework has seen extensive adoption, with a commendable number of installations and an active mailing list community engaging with the software. Additionally, survey feedback indicates a generally positive reception among users regarding the setup efficiency and overall ease of use provided by MoveIt!.

Limitations and Future Work

Despite the positive reception, the paper recognizes areas for future improvement, such as completing the setup of hardware controllers which may still present challenges for non-experts. Further development is also anticipated to refine user experiences and optimize the setup process. It is expected that continuing advancements in such frameworks will bolster easier integration of robotic software with advanced hardware systems.

Conclusion

This research underscores the significant need to evolve robotic frameworks that decrease barriers for potential users, driving broader usage and promoting greater innovation in robotics. By adopting strategies aligned with the entry barrier design principles presented, developers can expect to extend the reach of their software tools, enabling more contributors to engage effectively in complex robotics projects. Through MoveIt!, this work serves a seminal role in illustrating the path toward more accessible robotic software amid the gathering complexity of modern-day robotic systems.