Abstract
The wheel-legged hybrid robot (WLHR) is capable of adapting height and wheelbase configuration to traverse obstacles or rolling in confined space. Compared with legged and wheeled machines, it can be applied for more challenging mobile robotic exercises using the enhanced environment adapting performance. To make full use of the deformability and traversability of WHLR with parallel Stewart mechanism, this paper presents an optimization-driven planning framework for WHLR with parallel Stewart mechanism by abstracting the robot as a deformable bounding box. It will improve the obstacle negotiation ability of the high degree-of-freedoms robot, resulting in a shorter path through adjusting wheelbase of support polygon or trunk height instead of using a fixed configuration for wheeled robots. In the planning framework, we firstly proposed a pre-calculated signed distance field (SDF) mapping method based on point cloud data collected from a lidar sensor and a KD -tree-based point cloud fusion approach. Then, a covariant gradient optimization method is presented, which generates smooth, deformable-configuration, as well as collision-free trajectories in confined narrow spaces. Finally, with the user-defined driving velocity and position as motion inputs, obstacle-avoidancing actions including expanding or shrinking foothold polygon and lifting trunk were effectively testified in realistic conditions, demonstrating the practicability of our methodology. We analyzed the success rate of proposed framework in four different terrain scenarios through deforming configuration rather than bypassing obstacles.
Highlights
The legged machine shows its excellent adaptability of negotiating the convex obstacles.these actions necessitate substantial planning calculation [1], complicated model to sustain walking stability while swinging foot [2,3], and obstacle with a flat surface and relatively low height to maintain foothold safety [4]
Simulations are applied on a simulated BIT-NAZA robot model in Virtual Robot Experimentation Platform (V-REP) furnishing with VORTEX dynamic engine
All of the planning trajectories were created on the basis of signed distance field (SDF) representation of obstacle produced by point cloud data (PCD) and obstacle box dimension
Summary
The legged machine shows its excellent adaptability of negotiating the convex obstacles. These actions necessitate substantial planning calculation [1], complicated model to sustain walking stability while swinging foot [2,3], and obstacle with a flat surface and relatively low height to maintain foothold safety [4]. As legged robots have been developing to become popular, there is growing interest in incorporating benefits from the wheeled and legged mechanism to realize hybrid locomotion, intensifying the intention of boosting mobility and efficiency. Several wheel-legged hybrid robots (WLHRs) have shown their ability of adapting to convex environment. CENTAURO [5] which are equipped with steerable wheels on legs’ ending allows for executing steps, omnidirectional steering, and dominating a large variety of mobile manipulation missions, demonstrating its various moving modes in different types of terrains.
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