Design and comparative evaluation of an iterative contact point estimation method for static stability estimation of mobile actively reconfigurable robots

TL;DR: In this article, the authors propose a framework for resilient autonomous navigation in perceptually challenging unknown environments with mobility-stressing elements such as uneven surfaces with rocks and boulders, steep slopes, negative obstacles like cliffs and holes, and narrow passages.

TL;DR: A maneuver for negotiating surface discontinuities for a hybrid locomotion system consisting on a skid-steer wheeled vehicle with a single caster-leg mechanism is proposed, appropriate for gaps, steps, and ramps, both upwards and downwards.

TL;DR: In this paper, a self-supervised learning method for predicting the shape of supporting terrain (i.e. the terrain which will provide rigid support for the robot during its traversal) from sparse input measurements is proposed.

TL;DR: In this paper, an iterative geometric method that reduces the problem of robot pose prediction to two-dimensional image-processing operations by introducing the concept of a robot heightmap is presented.

TL;DR: This monograph discusses issues related to estimation, control, and motion planning for mobile robots operating in rough terrain, with particular attention to planetary exploration rovers.

TL;DR: This paper introduces a two-stage roadmap approach for motion planning in reconfigurable robots, enabling them to traverse rough terrain and obstacles by utilizing actuators and refining paths within constrained search spaces for enhanced mobility and safety.

TL;DR: Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.

TL;DR: The stability of legged machines in locomotion is considered and general machine has a rigid body to which legs are attached.