Task and motion planning for object manipulation in clutter
Goal: Develop algorithms to rearrange objects in cluttered and confined environments
Related articles/papers
J. Lee, Changjoo Nam, J. Park, and C. Kim, "Efficient Planning for Object Rearrangement by Local and Optimal Search in Clutter," IEEE Access, 2022.
J. Lee, U. Rakhman, Changjoo Nam, S. Kang, J. Park, and C. Kim, "High Dimensional Object Rearrangement for Robot Manipulation in Highly Dense Configurations," Intelligent Service Robotics (ISR), 2022.
Changjoo Nam, S. H. Cheong, J. Lee, D. H. Kim, and C. Kim, "Fast and resilient manipulation planning for object retrieval in cluttered and confined environments," IEEE Trans. on Robotics (T-RO), 2021.
J. Ahn, J. Lee, S. H. Cheong, C. Kim, Changjoo Nam, "An integrated approach for determining objects to be relocated and their goal positions inside clutter for object retrieval," IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. (BK21+ CS Top Conference)
J. Lee, Changjoo Nam, J. Park, C. Kim, ``Tree Search-based Task and Motion Planning with Prehensile and Non-prehensile Manipulation for Obstacle Rearrangement in Clutter,'' IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. (BK21+ CS Top Conference)
S. Cheong, B. Y. Cho, J. Lee, J. Lee, D. H. Kim, Changjoo Nam, C. Kim, and S.-K. Park, "Obstacle Rearrangement for Manipulation in Clutter using a Deep Q Network," Intelligent Service Robotics (ISR), 2021.
Changjoo Nam, J. Lee, S. Cheong, B. Y. Cho, and C. Kim, “Fast and resilient manipulation planning for target retrieval in clutter,” IEEE Int. Conf. on Robotics and Automation (ICRA), 2020. (BK21+ CS Top Conference)
S. Cheong, B. Y. Cho, J. Lee, C. Kim, and Changjoo Nam, “Where to relocate?: Object rearrangement inside cluttered and confined environments for robotic manipulation,” IEEE Int. Conf. on Robotics and Automation (ICRA), 2020. (BK21+ CS Top Conference )
Changjoo Nam, S. Lee, J. Lee, S. H. Cheong, D. H. Kim, C. Kim, I. Kim, and S.-K. Park, “A software architecture for service robots manipulating objects in human environments,” IEEE Access, 2020.
J. Lee, Y. Cho, Changjoo Nam, J. H. Park, and C. Kim, “Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments,” IEEE Int. Conf. on Robotics and Automation (ICRA), 2019. (BK21+ CS Top Conference)
Deep reinforcement learning for object manipulation
Goal: Develop technologies for human-level visuo-tactile sensing for object manipulation of soft-shell deformable objects
Collaborative work with Prof. Min-gu Kim at Inha University (https://wearablelinklab.com) and Prof. Sungeun Hong at SKKU (https://aim.skku.edu)
Deep reinforcement learning for industrial insertion
Goal: Develop an RL agent performing FPC insertion (flexible cable) task
Multi-robot coordination for object manipulation
Goal: Develop coordination algorithms for multiple manipulators for object rearrangement
Related articles/papers
Jeeho Ahn, C. Kim, and Changjoo Nam, "Coordination of two robotic manipulators for object retrieval in clutter," IEEE Int. Conf. on Robotics and Automation (ICRA), May 2022. (BK21+ CS Top Conference)
Jeeho Ahn, Sebin Lee, and Changjoo Nam, "Coordination of multiple mobile manipulators for ordered sorting of cluttered objects," accepted for presentation, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2023.
Multi-robot navigation
Goal: Develop path planning and navigation algorithms for multiple coordinated mobile robots
Multi-robot coordination in dynamic and uncertain environments
Goal: Develop algorithms to coordinate multiple robots to perform distributed tasks when costs are not deterministic
Related articles/papers
Changjoo Nam and D. A. Shell, “Robots in the Huddle: Upfront Computation to Reduce Global Communication at Run-time in Multi-Robot Task Allocation,” IEEE Trans. on Robotics (T-RO), Feb 2020.
W. Luo, Changjoo Nam, G. Kantor, and K. Sycara, “Decentralized Environmental Modeling and Adaptive Sampling for Multi-Robot Sensor Coverage,” Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2019. (BK21+ CS Top Conference)
S. Yi, Changjoo Nam, and K. Sycara, “Indoor Pursuit-Evasion with Hybrid Hierarchical Partially Observable Markov Decision Processes for Multi-Robot Systems,” Int. Symp. on Distributed Autonomous Robotic Systems (DARS), Oct 2018.
W. Luo, Changjoo Nam, K. Sycara, “Online Decision Making for Stream-based Robotic Sampling via Submodular Optimization,” IEEE Int. Conf. on Multisensor Fusion and Integration for Intelligent Systems (MFI), Nov 2017.
Changjoo Nam and D. A. Shell, "Analyzing the sensitivity of the optimal assignment in probabilistic multi-robot task allocation," IEEE Robotics and Automation Letters (RA-L), Jan 2017.
Changjoo Nam and D. A. Shell, "Bundling policies for sequential stochastic tasks in multi-robot systems," Int. Symp. on Distributed Autonomous Robotic Systems (DARS), Nov 2016.
Changjoo Nam and D. A. Shell, "Assignment Algorithms for Modeling Resource Contention in Multi-Robot Task Allocation," IEEE Trans. on Automation Science and Engineering (T-ASE), Jul 2015.
Changjoo Nam and D. A. Shell, "When to do your own thing: Analysis of cost uncertainties in multi-robot task allocation at run-time," IEEE Int. Conf. on Robotics and Automation (ICRA), May 2015. (BK21+ CS Top Conference)
Changjoo Nam and D. A. Shell, "Assignment Algorithms for Modeling Resource Contention and Interference in Multi-Robot Task-Allocation," IEEE Int. Conf. on Robotics and Automation (ICRA), May 2014. (BK21+ CS Top Conference)
Visual task planning for mobile navigation using a neurosymbolic model
Goal: Generate symbolic task plans for navigation from images capturing valid state transitions
Related articles/papers
U. Rakhman, J. Ahn, and Changjoo Nam, "Fully automatic data collection for neuro-symbolic task planning for mobile robot navigation," IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC), 2021.
Design of social behaviors for human-robot interaction
Goal: Design robot behaviors that can make users feel comfortable
Related articles/papers
Y.-J. Chae, Changjoo Nam, D. Yang, H. Sin, C. Kim, and S.-K. Park, "Generation of co-speech gestures of robot based on morphemic analysis," Robotics and Autonomous Systems (RAS), 2022.
D. Yang, Y.-J. Chae, D. Kim, Y. Lim, D. H. Kim, C. Kim, S.-K. Park, and Changjoo Nam, "Effects of social behaviors of robots in privacy-sensitive situations," Int. Journal of Social Robotics (IJSR), Jul 2021.
Human factors in supervisory control of multiple robots with swarm behaviors
Goal: Model human trust computationally while the human controls a swarm of robots in a supervisory fashion
Related articles/papers
Changjoo Nam, P. Walker, H. Li, M. Lewis, and K. Sycara, "Models of Trust in Human Control of Swarms with Varied Levels of Autonomy," IEEE Trans. on Human-Machine Systems (T-HMS), May 2020.
R. Liu, F. Jia, W. Luo, M. Chandarana, Changjoo Nam, M. Lewis, and K. Sycara, “Trust-Aware Behavior Reflection for Robot Swarm Self-Healing,” Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2019. (BK21+ CS Top Conference)
Changjoo Nam, H. Li, S. Li, M. Lewis, and K. Sycara, “Trust of Humans in Supervisory Control of Swarm Robots with Varied Levels of Autonomy,” IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC), Oct 2018.
J. Bang, H. Li, S. Nagavalli, Changjoo Nam, M. Lewis, and K. Sycara, “Human Interaction Through an Optimal Sequencer to Control Robotic Swarms,” IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC), Oct 2018.
Changjoo Nam, P. Walker, M. Lewis, and K. Sycara, "Predicting Trust in Human Control of Swarms via Inverse Reinforcement Learning," IEEE Int. Symposium on Robot and Human Interactive Communication (RO-MAN), Lisbon, Portugal, Aug 2017.