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Upper- and lower-limb motor dysfunction due to stroke, incomplete spinal cord injury, traumatic brain injury, and orthopedic conditions represents a major cause of long-term disability, with limited access to intensive, high-repetition rehabilitation in resource-constrained settings such as Bangladesh. Conventional physiotherapy, while effective, is often constrained by therapist workload, time limitations, and difficulty consistently delivering the volume of task-specific repetition believed necessary to drive neuroplastic recovery. Robotic rehabilitation systems offer programmable, high-repetition, objectively monitored movement training that can supplement conventional therapy, but evidence supporting their feasibility, safety, and effectiveness remains largely derived from high-income settings, with limited data from low- and middle-income countries. This prospective, parallel-group, two-arm pilot randomized controlled trial will be conducted at the Robotic Rehabilitation Centre, Department of Physical Medicine and Rehabilitation, Bangladesh Medical University (BMU). It will evaluate four robotic rehabilitation platforms manufactured by Shandong ZEPU Medical Technology Co., Ltd: the ZEPU-AI2 (upper-extremity feedback training and evaluation system), ZEPU-AI4 (multi-joint isokinetic training and evaluation system for upper and lower limb joints), ZEPU-AI6 Plus (three-dimensional robotic upper-limb active/passive training system), and ZEPU-AI7A (upper and lower limb active/passive rehabilitation system using motor-driven circular motion). Each device supports active, passive, and active-assisted training modes with adjustable resistance, range of motion, and assistance level, along with integrated safety features such as emergency stop mechanisms, motion limits, and, in some systems, spasm-detection and protection functions. A total of 36 participants will be randomly allocated in a 1:1 ratio to a robotic-augmented rehabilitation arm (standard-of-care rehabilitation plus supervised robotic-assisted therapy) or a usual-care control arm (standard-of-care rehabilitation alone). The intervention phase will run for 12 weeks, with robotic sessions delivered three times weekly (approximately 45 minutes per session, including donning/doffing and warm-up/cool-down), followed by a period of follow-up. Sessions will be supervised throughout by trained physiatrists and physiotherapists, with structured pre-session screening (vital signs, skin integrity, pain), safety harnessing during initial sessions as needed, and post-session skin and fatigue checks. Training parameters will be progressively adjusted on an individualized basis according to participant tolerance and performance. Assessments will be performed at baseline and at two-week intervals throughout the intervention and follow-up periods, using a battery of validated motor, strength, balance, gait, spasticity, pain, and functional-independence measures, together with device-recorded performance metrics (e.g., repetitions, torque, range of motion, training duration). Safety will be monitored through structured adverse event and serious adverse event reporting, with oversight from a Data Safety Monitoring Committee and a manufacturer-linked reporting pathway; predefined pause rules apply if more than two device-attributable serious adverse events occur. Feasibility and usability will be assessed through recruitment and screening metrics, session adherence and dropout rates, staff training/setup time, and a participant usability questionnaire administered at study completion. Statistical analysis will use an intention-to-treat approach as primary, with a per-protocol analysis as secondary. Continuous efficacy variables will be summarized as mean ± SD (or median/IQR where non-normally distributed) at each time point, with paired and unpaired comparisons as appropriate; a two-tailed p-value \< 0.05 will be considered statistically significant. This pilot study is intended to generate local, context-specific evidence on the feasibility, safety, and preliminary therapeutic potential of multi-platform robotic rehabilitation in Bangladesh, to inform the design of a future, adequately powered, large-scale randomized controlled trial and to support clinical and policy decision-making around robotic rehabilitation services.