Giri Wahyu Wiriasto, Siti Sendari, Dyah Lestari, Muhamad Syamsu Iqbal, Norrima Mochtar
The growing demand for energy-efficient robotic systems has driven research on energy-conscious trajectory planning and control for manipulators, yet findings remain scattered across methods and evaluation schemes. This systematic literature review aims to clarify how energyconscious concepts are formulated and implemented in trajectory research and to classify the links between analytic–numeric optimization and reinforcement-learning-based approaches. Following PRISMA guidelines, we queried Scopus (Springer and IJRCS) for journal articles published between 2021 and August 2025 and identified 124 primary studies. A structured extraction form and a taxonomy scheme mapped each paper to four research questions: (i) energy formulation, (ii) trajectory methods, (iii) system models and evaluation setups, and (iv) research gaps and future directions. Synthesis combined descriptive statistics with matrix-based and qualitative analysis. Results show that explicit energy-conscious formulations (energy models, torque or jerk penalties, power limits) appear only in a subset of works, while most studies still optimize indirect quantities such as time, smoothness, or tracking error. One-DoF configurations are frequently used as controlled testbeds for dynamics-and analytics-based energy studies. Kinematic or trajectory-based analytics and dynamics dominate the corpus (proportions 0.77 and 0.60), whereas hybrid, numeric and heuristic, and ML-or RL-based methods are less prevalent. Among the 22 studies that explicitly address energy-conscious aspects, these proportions increase to 0.96 and 0.86, indicating that analytic– dynamic formulations currently form the backbone of energy-efficient trajectory research while leaving substantial room for deeper integration between trajectory optimization and learning-based control. The review outlines priorities for multi-DoF energy models, real-time control, and energy-aware RL. © 2025 The Authors.
Departement of Electrical Engineering and Informatics, Universitas Negeri Malang, Malang, 65145, Indonesia; Departement of Electrical Engineering, Universitas Mataram, Mataram, 63115, Indonesia; Faculty of Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia
