Journal of Intelligent & Robotic Systems

About the journal

The Journal of Intelligent and Robotic Systems (JINT) aims at publishing the most recent advances in the fields of systems and control, robotics and automation, mechatronics, unmanned systems, machine intelligence, bioengineering and other related areas in which cutting edge technologies have been developed and applied to model, design, develop and test complex engineering systems and autonomous systems. The main objective of JINT is to publish peer-reviewed and original contributed papers, invited and survey papers that promote and disseminate scientific knowledge and information to the readers. Recognizing the importance of Unmanned Systems (or, Unmanned Vehicle Systems, UVS) for both civilian/public domain and military applications, JINT has a special section in each issue devoted to Unmanned Systems, focusing on all four classes of aerial, ground, sea-surface and underwater vehicles, the common characteristic of which is the absence on-board the vehicle of a human operator. As Unmanned Systems have seen unprecedented levels of growth over the last twenty years, and they are expected to dominate future applications in diverse domains, JINT is at the forefront of reporting scientific breakthroughs in UVS. The Journal of Intelligent and Robotic Systems covers the whole technical spectrum from the birth of an idea at the conceptual level to a potential product development. It publishes original, archival, peer reviewed contributions from the initial concept, to theory, to simulation, to validation and verification, to experimentation, to prototyping, to testing, to implementation and refinement, to final product development and commercialization. It provides a unique forum that bridges gaps between the diverse disciplines of System Theory, Mathematics, Computer Science, Artificial Intelligence and Engineering, extending to the matured field of Soft Computing, as well as to the field of Computational Intelligence and Cognitive Sciences, all necessary components of modern intelligent systems, robotics, unmanned vehicle systems, mechatronics and modern manufacturing. JINT provides a unique medium to present/discuss future directions in advanced control technology and applications, intelligent and autonomous systems, computational intelligence, computational methods for system design, handling and incorporating uncertainty in system design and control, novel and cutting edge technologies as applied to complex systems including mechatronic systems and unmanned vehicle systems.

Articles

• Eurico Pedrosa, Artur Pereira, Nuno Lau. A Non-Linear Least Squares Approach to SLAM using a Dynamic Likelihood Field. Journal of Intelligent & Robotic Systems, vol. 93, no. 3-4, p. 519-532, March 2019
• Abbas Abdolmaleki, David Simões, Nuno Lau, Luis Paulo Reis, Gerhard Neumann. Contextual Direct Policy Search: With Regularized Covariance Matrix Estimation. Journal of Intelligent & Robotic Systems, vol. 96, no. 2, p. 141-157, November 2019
• Abbas Abdolmaleki, Nuno Lau, Luis Paulo Reis, Jan Peters, Gerhard Neumann. Contextual policy search for linear and nonlinear generalization of a humanoid walking controller. Journal of Intelligent & Robotic Systems, vol. 83, no. 3, p. 393-408, September 2016
• Vahid Mokhtari, Luís Seabra Lopes, Armando J. Pinho. Experience-Based Planning Domains: an Integrated Learning and Deliberation Approach for Intelligent Robots. Journal of Intelligent & Robotic Systems, vol. 83, no. 3, p. 463-483, September 2016
• José Rosado, Filipe Silva, Vitor Santos, António Amaro. Adaptive Robot Biped Locomotion with Dynamic Motion Primitives and Coupled Phase Oscillators. Journal of Intelligent & Robotic Systems, vol. 83, no. 3, p. 375–391, September 2016
• Nuno Lau, António Paulo Moreira, Rodrigo Ventura, Brígida Mónica Faria. Special Issue Robótica 2014. Journal of Intelligent & Robotic Systems, vol. 80, no. 3, p. 363-364, December 2015
• Brígida Mónica Faria, Luis Paulo Reis, Nuno Lau. Adapted Control Methods for Cerebral Palsy Users of an Intelligent Wheelchair. Journal of Intelligent & Robotic Systems, vol. 77, no. 2, p. 299-312, February 2015
• João Cunha, Rui Serra, Nuno Lau, Luís Seabra Lopes, António J. R. Neves. Batch Reinforcement Learning for Robotic Soccer Using the Q-Batch Update-Rule. Journal of Intelligent & Robotic Systems, vol. 80, no. 3, p. 385-399, December 2015
• Brígida Mónica Faria, Luis Paulo Reis, Nuno Lau. A Methodology for Creating an Adapted Command Language for Driving an Intelligent Wheelchair. Journal of Intelligent & Robotic Systems, vol. 80, no. 3, p. 609-623, December 2015
• Hamidreza Kasaei, Miguel Riem Oliveira, Gi Hyun Lim, Luís Seabra Lopes, Ana Maria Tomé. Interactive Open-Ended Learning for 3D Object Recognition: An Approach and Experiments. Journal of Intelligent & Robotic Systems, vol. 80, no. 3, p. 537-553, December 2015
• Nima Shafii, Nuno Lau, Luis Paulo Reis. Learning to Walk Fast: Optimized Hip Height Movement for Simulated and Real Humanoid Robots. Journal of Intelligent & Robotic Systems, vol. 80, no. 3, p. 555-571, December 2015

Impact factor

The impact factor of Journal of Intelligent & Robotic Systems is as follows: