WMMOVE

WMMOVE is a modular open-source framework for motion planning and optimization designed to generate smooth, feasible trajectories for robotic manipulators, autonomous agents, and animated characters. The system prioritizes a balance between responsiveness and physical plausibility by integrating trajectory representation, constraint handling, and trajectory smoothing. A notable feature is the use of a weighted moving average–based filter applied to candidate trajectories during optimization to improve smoothness without sacrificing goal criteria.

Origin and development plans place WMMOVE in the mid-2010s, arising from a collaborative effort among researchers in robotics and computer graphics who sought a common platform for experimenting with motion-planning pipelines. The project has evolved through community contributions and is maintained in an ongoing, open development process with public releases and documentation.

Architecture and components of WMMOVE include a trajectory representation layer (waypoints with timestamps), planning modules (global and local planners), an optimization core (supporting multiple solvers and objective terms), and a constraint engine (handling joint limits, velocity and acceleration bounds, and task-specific constraints). The framework also provides collision checking, simulation backends, and visualization tools. Interoperability is emphasized via standard interfaces and adapters for ROS, Gazebo, and similar environments, enabling integration with common robotics and animation workflows.

Algorithms and methods focus on combining optimization-based and sampling-based techniques, with the weighted moving average smoothing playing a central role in producing natural motion. Cost functions typically account for path length, travel time, energy, and jerk, while constraints are enforced through penalty or barrier formulations.

Usage and reception: WMMOVE is used in academic research and hobbyist projects to prototype motion-planning pipelines and evaluate smoothing strategies. Its modular design invites experimentation, though practitioners note that tuning parameters can affect performance and stability. See also related topics in motion planning and trajectory optimization.