Lookahead Navigation for High-Speed Mobile Robots

Recent developments in both defense and commercial sectors have inspired a growing interest in mobile robot navigation technologies. As look-ahead sensing capabilities improve, mobile robots will be able to operate at higher speeds and in more varied environments. This research aims to develop novel planning and control approaches to meet the challenge.

Operation at high speeds requires the anticipation of obstacles and terrain changes. In addition, dynamic effects such as friction saturation and loss of ground contact limit the class of feasible vehicle trajectories. A lookahead naviation system must be capable of planning a feasible trajectory through the sensed environment and controlling the vehicle along that trajectory while remaining robust to terrain changes and dynamic disturbances.

To achieve this kind of forward-looking, versatile control, we are leveraging the prediction and constraint-handling capabilities of model predictive control. Model Predictive Control (MPC) is a flexible, model-based control approach that seeks to minimize an objective function by optimizing a projected set of control inputs over a progressive and forward-looking time horizon. Its ability to explicitly consider constraints, track references, include environmental disturbances, and incorporate multiple actuation methods make it particularly well-suited for the mobile robot navigation problem.