Curved Patch Mapping and Tracking for Irregular Terrain Modeling: Application to Bipedal Robot Foot Placement
Dimitrios Kanoulas, Nikos G. Tsagarakis and Marsette Vona
Abstract — Legged robots need to make contact with irregular surfaces, when operating in unstructured natural terrains. Representing
and perceiving these areas to reason about potential contact between a robot and its surrounding environment, is still largely an open
problem. This paper introduces a new framework to model and map local rough terrain surfaces, for tasks such as bipedal robot foot
placement. The system operates in real-time, on data from an RGB-D and an IMU sensor. We introduce a set of parameterized patch
models and an algorithm to fit them in the environment. Potential contacts are identified as bounded curved patches of approximately
the same size as the robot’s foot sole. This includes sparse seed point sampling, point cloud neighborhood search, and patch fitting
and validation. We also present a mapping and tracking system, where patches are maintained in a local spatial map around the robot
as it moves. A bio-inspired sampling algorithm is introduced for finding salient contacts. We include a dense volumetric fusion layer for
spatiotemporally tracking, using multiple depth data to reconstruct a local point cloud. We present experimental results on a mini-biped
robot that performs foot placements on rocks, implementing a 3D foothold perception system, that uses the developed patch mapping
and tracking framework.
Index Terms — irregular surface modeling, foothold contact modeling, bounded curved patch modeling, curved patch fitting and
tracking, 3D perception for bipedal robots, bipedal robot foot placement, rough terrain stepping, legged robot locomotion