A method of reactive control for 3D navigation of a nonholonomic robot in tunnellike environments Abstract   A nonholonomic underactuated robot with a bounded control range travels inside an unknown and unstructured 3D tunnel bounded by a generic 2D surface. The robot has access to the nearest point of the surface and measures the distance to the surface along any ray from a narrow beam emitted from the robot around the direction to the nearest point. We present a new navigation law that ensures constant advancement of the robot through the tunnel, along with respecting a given safety margin to its surface, driving the robot to the desired distance to it, and subsequently maintaining this distance. This law is reactive: it generates the current control as a reflexlike reaction to the current observation. Rigorous justification of the proposed guidance approach is provided; its applicability and performance are confirmed by computer simulation tests.

Optimal Steering of Stochastic Mobile Robots that Undergo Collisions with their Environment The paper introduces a statefeedback closedloop control approach with integrated collision exploitation. We represent the systemxe2x80x99s kinematics in the form of a driftdiffusion stochastic differential equation, and follow a stochastic switching framework to model the transition between states of free motion and in collision with the environment. We formulate an optimal steering problem and compute the control input related to state feedback. Collisions are found beneficial in terms of increasing task success probability when steering a robot from an initial to a target spatial distribution. In certain cases, collisions may help reduce the control energy for the task when compared to optimal steering with collision avoidance. We provide a mathematical basis to explain this finding, perform several parametric analyses in simulation to validate the theoretical analysis, and conduct realistic physics simulations to quantify the impact of realistic constraints (bounded control input, physical impact of collision, and friction) on control energy and success probability. Further, we validate the proposed approach experimentally with an omnidirectional collisionresilient wheeled robot.