Sampling‐based hierarchical motion planning for a reconfigurable wheel‐on‐leg planetary analogue exploration rover

Abstract

Reconfigurable mobile planetary rovers are versatile platforms that may safely traverse cluttered environments by morphing their physical geometry. Planning paths for these adaptive robots is challenging due to their many degrees of freedom, and the need to consider potentially continuous platform reconfiguration along the length of the path. We propose a novel hierarchical structure for asymptotically optimal (AO) sampling‐based planners and specifically apply it to the state‐of‐the‐art Fast Marching Tree (FMT*) AO planner. Our algorithm assumes a decomposition of the full configuration space into multiple subspaces, and begins by rapidly finding a set of paths through one such subspace. This set of solutions is used to generate a biased sampling distribution, which is then explored to find a solution in the full configuration space. This technique provides a novel way to incorporate prior knowledge of subspaces to efficiently bias search within existing AO sampling‐based planners. Importantly, probabilistic completeness and asymptotic optimality are preserved. Experimental results in simulation are provided that benchmark the algorithm against state‐of‐the‐art sampling‐based planners without the hierarchical variation. Additional experimental results performed with a physical wheel‐on‐leg platform demonstrate application to planetary rover mobility and showcase how constraints such as actuator failures and sensor pointing may be easily incorporated into the planning problem. In minimizing an energy objective that combines an approximation of the mechanical work required for platform locomotion with that required for reconfiguration, the planner produces intuitive behaviors where the robot dynamically adjusts its footprint, varies its height, and clambers over obstacles using legged locomotion. These results illustrate the generality of the planner in exploiting the platform's mechanical ability to fluidly transition between various physical geometric configurations, and wheeled/legged locomotion modes, without the need for predefined configurations.

Path Planning for Autonomous Mobile Robots: A Review

“…To the authors’ knowledge there are not many existing Local Planning approaches addressing the kinodynamic constraints of robots with multiple locomotion modes. Reid et al [ 50 ] proposed the use of a Sampling-Based algorithm, the Fast Marching Tree (FMT*), to tackle the motion planning of a reconfigurable hybrid robot with wheeled-legs.…”

“…The main objective of FMT* is to find paths, avoiding obstacles, in problems involving a high number of degrees of freedom. One example of this is the motion planning of an articulated vehicle presented by Reid et al [ 50 ]. Ichter et al [ 199 ] propose the use of Group Marching Tree (GMT*), a similar algorithm to FMT* but which focuses on speeding up computation via parallelization using GPUs.…”

Rough Terrain Navigation for Legged Robots using Reachability Planning and Template Learning

“…Dynamic planning using a reduced robot model has recently shown promising results [21] but has not been evaluated in deployment scenarios. Other work on navigation planning specifically for legged robots either only considers cases of obstacle avoidance on flat terrain [22], [23] or does additional contact planning, which pushes computational complexity past the real-time mark [24], [25], [26].…”

Adaptive sampling with an autonomous underwater vehicle in static marine environments

“…To avoid discretization of the environment, Hitz et al (2017) use evolutionary techniques to optimize a parameterized B-spline in continuous space. Further, Reid et al (2020) explore hierarchical informative planning with applications to sampling using reconfigurable systems such as a planetary rover. Additional approaches to informative path planning based on hypothesis testing (Lim et al, 2016), fast marching methods (Lawrance et al, 2017), and orienteering (Bottarelli et al, 2019) have also been proposed.…”