The Electrical engineering undergraduate program of the Escola Politécnica of the Universidade de São Paulo has created an alternative innovative curriculum path for its freshmen students in 2024. The Compet...
详细信息
LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle varia...
详细信息
Automated vehicle acceptance (AVA) has been measured mostly subjectively by questionnaires and interviews, with a main focus on drivers inside automated vehicles (AVs). To ensure that AVs are widely accepted by the pu...
详细信息
This work proposes a complete autonomous navigation system for a tracked vehicle. The system enables a complete autonomous execution of waypoint and patrolling tasks selected by the user. It also enables user-vehicle ...
详细信息
This work proposes a complete autonomous navigation system for a tracked vehicle. The system enables a complete autonomous execution of waypoint and patrolling tasks selected by the user. It also enables user-vehicle shared autonomy, switching between the user teleoperation and the vehicle autonomous operation. Our navigation system uses the model predictive control scheme based on a navigation function. We propose the navigation function which takes into account changing environments, any-shape footprint, and non-holonomic motion of the tracked vehicle. Besides the waypoint and patrolling tasks, we implemented a fail-safe scenario in case of the user-vehicle communication loss, in which the vehicle returns autonomously to the previously visited goal where the communication was stable. The efficiency of the proposed system is validated by experimental results on the Komodo tracked vehicle.
This paper considers the distributed robust suboptimal consensus control problem of linear multi-agent systems, with both H2 and H∞ performance requirements. A novel two-step complementary design approach is proposed...
详细信息
Digitalization of health, healthcare and healthcare delivery unequivocal have positive consequences contributing to health system goals, but they also might have some negative ones which have to be avoided or mitigate...
详细信息
The success of a cooperative manipulation process depends on the level of disturbance rejection between the cooperating agents. However, this attribute may be jeopardized due to unexpected behaviors, such as joint sat...
详细信息
ISBN:
(数字)9781665467612
ISBN:
(纸本)9781665467629
The success of a cooperative manipulation process depends on the level of disturbance rejection between the cooperating agents. However, this attribute may be jeopardized due to unexpected behaviors, such as joint saturation or internal collisions. This leads to deterioration in the performance of the manipulation task. In this paper, we present an adaptive distributed control framework that directly mitigates these internal disturbances, both in the joint (and task) spaces. With our approach, we show that including the manipulator-load coupling in the definition of the task error yields improved performance and robustness. To validate this statement, we provide stability guarantees and simulation results for two implementation cases.
The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics o...
The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines.
Feedforward control with task flexibility for MIMO systems is essential to meet ever-increasing demands on throughput and accuracy. The aim of this paper is to develop a framework for data-driven tuning of rational fe...
Feedforward control with task flexibility for MIMO systems is essential to meet ever-increasing demands on throughput and accuracy. The aim of this paper is to develop a framework for data-driven tuning of rational feedforward controllers in iterative learning control (ILC) for noncommutative MIMO systems. A convex optimization problem in ILC is achieved by rewriting the nonlinear terms in the control scheme as a function of the previous feedforward parameters. A simulation study on an multivariable industrial printer shows that the developed framework converges and achieves significant better performance than direct application of the RBF algorithm using SK-iterations for SISO systems.
Humans have the ability to deviate from their natural behavior when necessary, which is a cognitive process called response inhibition. Similar approaches have independently received increasing attention in recent yea...
Humans have the ability to deviate from their natural behavior when necessary, which is a cognitive process called response inhibition. Similar approaches have independently received increasing attention in recent years for ensuring the safety of control. Realized using control barrier functions or predictive safety filters, these approaches can effectively ensure the satisfaction of state constraints through an online adaptation of nominal control laws, e.g., obtained through reinforcement learning. While the focus of these realizations of inhibitory control has been on risk-neutral formulations, human studies have shown a tight link between response inhibition and risk attitude. Inspired by this insight, we propose a flexible, risk-sensitive method for inhibitory control. Our method is based on a risk-aware condition for value functions, which guarantees the satisfaction of state constraints. We propose a method for learning these value functions using common techniques from reinforcement learning and derive sufficient conditions for its success. By enforcing the derived safety conditions online using the learned value function, risk-sensitive inhibitory control is effectively achieved. The effectiveness of the developed control scheme is demonstrated in simulations.
暂无评论