  This paper presents a trajectory planning method for wheeled robots with
fixed steering axes while the steering angle of each wheel is constrained. In
the past, All-Wheel-Steering(AWS) robots, incorporating modes such as
rotation-free translation maneuvers, in-situ rotational maneuvers, and
proportional steering, exhibited inefficient performance due to time-consuming
mode switches. This inefficiency arises from wheel rotation constraints and
inter-wheel cooperation requirements. The direct application of a holonomic
moving strategy can lead to significant slip angles or even structural failure.
Additionally, the limited steering range of AWS wheeled robots exacerbates
nonlinearity issues, thereby complicating control processes. To address these
challenges, we developed a novel planning method termed Constrained AWS(C-AWS),
which integrates second-order discrete search with predictive control
techniques. Experimental results demonstrate that our method adeptly generates
feasible and smooth trajectories for C-AWS while adhering to steering angle
constraints.
