Autonomous Modification of Unstructured Environments with Found Material

The ability to autonomously modify their environment dramatically increases the capability of robots to operate in unstructured environments. We develop a specialized construction algorithm and robotic system that can autonomously build motion support structures with previously unseen objects. The approach is based on our prior work on adaptive ramp building algorithms, but it eliminates the assumption of having specialized building materials that simplify manipulation and planning for stability. Utilizing irregularly shaped stones makes the problem significantly more challenging since the outcome of individual placements is sensitive to details of contact geometry and friction, which are difficult to observe. To reuse the same high-level algorithm, we develop a new physics-based planner that explicitly considers the uncertainty produced by incomplete in-situ sensing and imprecision during pickup and placement. We demonstrate the approach on a robotic system that uses a newly developed gripper to reliably pick up stones with minimal additional sensors or complex grasp planning. The resulting system can build structures with more than 70 stones, which in turn provide traversable paths to previously inaccessible locations.

Authors

• Vivek Thangavelu
• Maíra Saboia da Silva
• Jiwon Choi
• Nils Napp

Keywords

• Uncertainty
• Robot sensing systems
• Physics
• Shape
• Buildings
• Unstructured Environments
• Adaptive Algorithm
• Robotic System
• Building Materials
• Construction Algorithm
• Target Location
• Rigid Body
• Target Area
• Point Cloud
• Reasonable Time
• Major Axis
• Real-world Scenarios
• Position Error
• Ground Plane
• Path Planning
• Building Process
• Surface Reconstruction
• Assembly Step
• Physical Simulation
• Physics Engine
• Navigation Path
• Contour Points
• Forward Simulation
• Orientation Error
• physics simulation
• autonomous construction
• robotics
• irregular building materials.