The field of robotic systems and motion planning is moving towards more efficient and optimized solutions. Researchers are focusing on developing novel methodologies for designing and optimizing robotic systems, particularly in complex and cluttered environments. One of the key areas of research is the development of self-motion manifolds, which enable redundant manipulators to achieve desired end-effector poses while avoiding joint limits and obstacles. Another area of focus is the use of simulation-based planning for generating optimized motion sequences in multi-robot assembly cells. Noteworthy papers include:

• A Systematic Robot Design Optimization Methodology with Application to Redundant Dual-Arm Manipulators, which proposes a four-part design optimization methodology for automating the development of task-specific robotic systems.
• ODE Methods for Computing One-Dimensional Self-Motion Manifolds, which introduces a novel ODE formulation for computing self-motion manifolds using standard explicit fixed-step ODE integrators.