相关论文: Autonomous Emergency Collision Avoidance and Stabi…

In this paper, we propose an efficient and accurate method for autonomous surface vehicles to generate a smooth and collision-free trajectory considering its dynamics constraints. We decouple the trajectory planning problem as a front-end…

Online generation of collision free trajectories is of prime importance for autonomous navigation. Dynamic environments, robot motion and sensing uncertainties adds further challenges to collision avoidance systems. This paper presents an…

This paper proposes a novel approach to integrate optimal control of perimeter intersections (i.e. to minimize local delay) into the perimeter control scheme (i.e. to optimize traffic performance at the network level). This is a complex…

Evaluating and updating the obstacle avoidance velocity for an autonomous robot in real-time ensures robustness against noise and disturbances. A passive damping controller can obtain the desired motion with a torque-controlled robot, which…

This paper presents an optimization-based collision avoidance trajectory generation method for autonomous driving in free-space environments, with enhanced robustness, driving comfort and efficiency. Starting from the hybrid…

This paper presents a hierarchical longitudinal control architecture for autonomous truck platoons that jointly addresses safety, string stability, and economic efficiency. The framework integrates a high-rate safety projection filter, a…

This paper presents an autonomous control framework for articulated boom cranes performing prefabricated block assembly in construction environments. The key challenge addressed is precise placement control under passive joint dynamics that…

Drift control is significant to the safety of autonomous vehicles when there is a sudden loss of traction due to external conditions such as rain or snow. It is a challenging control problem due to the presence of significant sideslip and…

Action anticipation, intent prediction, and proactive behavior are all desirable characteristics for autonomous driving policies in interactive scenarios. Paramount, however, is ensuring safety on the road --- a key challenge in doing so is…

Cooperative vehicle coordination at unsignalized intersections has garnered significant interest from both academia and industry in recent years, highlighting its notable advantages in improving traffic throughput and fuel efficiency.…

Overtaking is one of the most challenging tasks in driving, and the current solutions to autonomous overtaking are limited to simple and static scenarios. In this paper, we present a method for behaviour and trajectory planning for safe…

This paper proposes a new control strategy to improve vehicle cornering performance in a model predictive control framework. The most distinguishing feature of the proposed method is that the natural handling characteristics of the…

We extend the behaviour of generic sample-based motion planners to support obstacle avoidance during long-range path following by introducing a new edge-cost metric paired with a curvilinear planning space. The resulting planner generates…

Safety in obstacle avoidance is critical for autonomous driving. While model predictive control (MPC) is widely used, simplified prediction models such as linearized or single-track vehicle models introduce discrepancies between predicted…

Recently, researchers have proposed various autonomous intersection management techniques that enable autonomous vehicles to cross the intersection without traffic lights or stop signs. In particular, a priority-based coordination system…

Autonomous vehicles must navigate dynamically uncertain environments while balancing safety and efficiency. This challenge is exacerbated by unpredictable human-driven vehicle (HV) behaviors and perception inaccuracies, necessitating…

In this paper, we present a real-time whole-body planner for collision-free legged mobile manipulation. We enforce both self-collision and environment-collision avoidance as soft constraints within a Model Predictive Control (MPC) scheme…

Safety guarantees in motion planning for autonomous driving typically involve certifying the trajectory to be collision-free under any motion of the uncontrollable participants in the environment, such as the human-driven vehicles on the…

In order for automated mobile vehicles to navigate in the real world with minimal collision risks, it is necessary for their planning algorithms to consider uncertainties from measurements and environmental disturbances. In this paper, we…

Autonomous vehicles are the upcoming solution to most transportation problems such as safety, comfort and efficiency. The steering control is one of the main important tasks in achieving autonomous driving. Model predictive control (MPC) is…