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The purpose of this paper is to present a visual servo tracking strategy for the wheeled mobile robot, where the unknown feature depth information can be identified simultaneously in the visual servoing process.

By using reference, desired and current images, system errors are constructed by measurable signals that are obtained by decomposing Euclidean homographies. Subsequently, by taking the advantage of the concurrent learning framework, both historical and current system data are used to construct an adaptive updating mechanism for recovering the unknown feature depth. Then, the kinematic controller is designed for the mobile robot to achieve the visual servo trajectory tracking task. Lyapunov techniques and LaSalle’s invariance principle are used to prove that system errors and the depth estimation error converge to zero synchronously.

The concurrent learning-based visual servo tracking and identification technology is found to be reliable, accurate and efficient with both simulation and comparative experimental results. Both trajectory tracking and depth estimation errors converge to zero successfully.

On the basis of the concurrent learning framework, an adaptive control strategy is developed for the mobile robot to successfully identify the unknown scene depth while accomplishing the visual servo trajectory tracking task.

The purpose of this study is to propose a path-planning strategy based on the velocity-virtual spring method to realize collision-free tasks in dynamic environments and further improve the effect.

By considering factors such as the relative velocity and direction of dynamic obstacles, the repulsive force of the robot is improved, thereby enhancing the adaptability of the strategy and achieving flexible and effective avoidance against dynamic obstacles. The attraction formula has been designed to allow the robot to have better smooth changes and higher gradients near the target, helping robots better reach the target and follow formations. Moreover, to meet the demands of the various stages during the driving process, the null space behavioral control is used to solve multi-task conflict problems and strengthen formation coordination and control.

Comparison of the planning path and formation effects through simulation and physical experiments, the results of this study show that the algorithm proposed can successfully maintain formation stability and plan smooth and safe paths in static or dynamic environments.

This paper proposes a path-planning strategy based on the velocity-virtual spring method to plan collision-free paths for formation in dynamic environments.

The purpose of this paper is to propose a new velocity prediction navigation algorithm to develop a conflict-free path for robots in dynamic crowded environments. The algorithm BP-prediction and reciprocal velocity obstacle (PRVO) combines the BP neural network for velocity PRVO to accomplish dynamic collision avoidance.

This presented method exhibits innovation by anticipating ahead velocities using BP neural networks to reconstruct the velocity obstacle region; determining the optimized velocity corresponding to the robot’s scalable radius range from the error generated by the non-holonomic robot tracking the desired trajectory; and considering acceleration constraints, determining the set of multi-step reachable velocities of non-holonomic robot in the space of velocity variations.

The method is validated using three commonly used metrics of collision rate, travel time and average distance in a comparison between simulation experiments including multiple differential drive robots and physical experiments using the Turtkebot3 robot. The experimental results show that our method outperforms other RVO extension methods on the three metrics.

In this paper, the authors propose navigation algorithms capable of adaptively selecting the optimal speed for a multi-robot system to avoid robot collisions during dynamic crowded interactions.

The formation of unmanned aerial vehicle (UAV) swarm plays a critical role in numerous applications, such as unmanned agriculture, environmental monitoring and cooperative fencing. Meanwhile, the self-organized swarm model exhibits excellent performance in amorphous formation flight, and its collective motion pattern displays great potential in dense obstacle avoidance. The paper aims to realize the formation maintenance of UAVs while combining the advantage of the self-organized swarm model in avoiding dense obstacles. Thereby enhancing the flexibility, adaptability and safety of UAV swarms in dense and unpredictable scenarios.

In this paper, a self-organized formation (SOF) swarm model with a constrained coordination mechanism is proposed. A global information-based formation rule is designed to flexibly maintain the formation. A constraint coordination mechanism is designed to resolve the problem of constraint conflicts between formation rules and self-organized behavior rules. The model introduces a new obstacle avoidance rule to prevent deadlocks. Extensive experiments including simulations, real flights and comparative experiments are conducted to evaluate the performance of the model.

The simulation results show that SOF swarm enables the formation elastically to dense obstacles. Compared to the Vasarhelyi model, swarm performance metrics are improved. For example, the task completion time of SOF swarm is reduced by 16%, 28% and 39% across the three obstacle densities, and the order of SOF swarm is improved by 4%, 13% and 18%, respectively. The proposed model is also validated with a swarm of seven quadcopters that can successfully navigate and maintain formation in a real-world indoor environment with dense obstacles. Video at: https://youtu.be/V8hYgOHxWls.

The proposed formation rule is based on global information construction, which presents challenges in terms of communication overhead in distributed systems.

An SOF swarm model is proposed, which achieves formation maintenance by incorporating formation rule and constraint coordination mechanism and improves obstacle avoidance performance by introducing a new obstacle avoidance rule. After real UAVs verification, the model is feasible for practical deployment and provides a new solution to the formation flight and formation maintenance problems encountered in dense environments.

The authors empirically examine the impact of the stand-alone risk committee on corporate risk-taking and firm value.

The authors argue that the existence of a stand-alone risk committee enhances the quality of corporate governance, which reduces corporate risk-taking and strengthens the firm value that might improve investor protection.

The authors find corporate risk-taking decline significantly for firms that have a stand-alone risk committee compared with firms that have a joint audit and risk committee. The authors also find that the presence of a stand-alone risk committee is positively associated with firm value.

The evidence is consistent with the proposition that firms with a stand-alone risk committee can effectively evaluate potential risks and implement a proper risk management system.

This is the first paper that investigates the association between the existence of a stand-alone risk committee and firm risk-taking in a multi-industry setting. Also, our research extends the association between a stand-alone risk committee and firm value.

This study aims to explore key factors and specific ways for the upgrade to hybrid incubators in the context of China. A hybrid incubator means that a technology-based business incubators (TBIs) can implement various distinct value creation processes with the integration of the advantages of non-for-profit and for-profit TBIs at same time as Chinese government now requires government-sponsored non-for-profit TBIs to be profitable self-sustainability with less dependent on direct public subsidies, aiming to motivate these TBIs to provide higher quality services for their tenant new technology-based firms (NTBFs).

This study conducts a single in-depth case-study of Tuspark Incubator (located in Tsinghua Science Park [TSP]) with categorical analysis.

Three factors, i.e. incubation subdivision, intermediary platform and proactive approach, are found to be essential for a formerly government-sponsored TBI’s upgrading. Incubation subdivision enables Tuspark Incubator to create multiple incubation processes with incubator characteristic variables of both non-for-profit and for-profit incubators; with the establishment of intermediary platform, Tuspark Incubator provides specialized business support and high-quality networking from relevant specialized service organizations external to the incubator; more proactive approach with equity investment on incubating firms from Tuspark Incubator help to generate social welfare and financial profit at the same time.

For the incubators’ managers, incubation subdivision enables TBIs to operate for-profit and non-for-profit processes at the same time and provides different specific needs; more open intermediary service platforms can leverage the full potential of the actors in innovation system and help TBIs to save resource when upgrading to hybrid incubators; proactive approaches nurture learning climate and entrepreneurship environment to enhance the successful rate on NTBFs inside incubators and provide main profit source for incubators. For policy makers, using proactive approaches including creating a good milieu for incubation on technology-based start-ups and the design of public guidance funds is increasingly crucial.

This research is a pioneering study on the key factors and specific ways for the upgrade of government-sponsored non-for-profit TBIs in China to hybrid for-profit and non-for-profit incubators.

The purpose of this paper is to explore and highlight the particular innovation characteristics and modes of the Chinese online game industry from a networking perspective.

This research is qualitative. Both primary and secondary data are used, which is collected through desk research on related documents and long‐term participative observation and personal experiences. This paper begins with an overview of the online game industry's innovation process and types; then constructs a framework that contains four innovation modes with different networks to guide the analysis and organization on the empirical findings; finally, the paper proposes some implications for companies and government.

This paper is an attempt to open the black box of the innovation of the Chinese online game industry. Born as an incomplete and virtual product, the innovation modes evolve from closed to a combination of open and networking ones. Producer‐driven Innovation Network Mode shows that game companies can get innovation resources through its focal network. Producer‐user Interaction Mode shows that players' have tremendous innovation potential. Open Collaborative Network Mode shows that power is distributed and the roles of actors are blurred.

This paper offers an analysis of the Chinese online game industry from the innovation side and partly fills the research gap. Also, this paper emphasized the users' innovation ability and a hybrid of different innovation modes, which can be seen as a successful theory test of user innovation, innovation networks, and open innovation theories in the Chinese context.

The forest products processing industry is a key component of the forestry economy, and the level of companies’ operating efficiency directly affects its profitability and market competitiveness.

In order to deeply study the operation status of forest product processing industry, this paper takes the panel data of 70 listed forest product processing companies from 2015 to 2022 as the basis, and adopts BBC, CCR and DEA-Malmquist models to measure the operating efficiency of these companies. Meanwhile, the Tobit model is applied to deeply explore the impact of innovation input on operating efficiency.

The results of the paper show that: (1) the overall operating efficiency of listed forest product processing companies performs well, and the improvement of technology level promotes the growth of total factor productivity; (2) innovation input plays a significant positive role in listed forest product processing companies, which positively affects the operating efficiency.

A scientific and reasonable evaluation of the operating efficiency of listed forest product companies is of great practical significance to the development of the forestry industry The study of forest product processing industry is of key significance to the social economy.

This paper explores the improvement of production and operation efficiency of forest products processing enterprises for the purpose of in-depth analysis of the current situation of China's forest products processing enterprises, which is conducive to improving the innovation and operation efficiency of China's forest products processing enterprises, and realizing the high-quality development of China's forest products processing industry.