Table 1.
Related works involving smart walkers with the integration of interfaces for Human–Robot–Environment Interaction.
| Walker | Type | Sensory Interface |
Internal Modules | Modes of Operation |
Shared Control Strategies |
Social Interaction |
|---|---|---|---|---|---|---|
| GUIDO [22] | Active | - Force sensors - LRF - Sonars - Encoders |
- Autonomous navigation - Detection of user’s intentions - Sound feedback |
- Supervised - Autonomous |
- | - |
| XR4000 [23] | Active | - Force sensors - LRF - Sonars - Infrared sensors - Encoders |
- Autonomous navigation - Detection of user’s intentions |
- Free - Supervised - Autonomous |
Shared walker steering on active mode |
|
| ASBGo++ [21,24,25] |
Active | - Force sensors - LRF - Sonar - Infrared sensors - Camera - Encoders |
- Autonomous navigation - Detection of user’s intentions - Gait monitoring - User position feedback |
- Free - Supervised - Autonomous |
- | - |
| JARoW [26,27] | Active | - Infrared sensors - Encoders - LRFs |
- User position estimation and prediction - Obstacle avoidance |
- Free - Supervised |
- | - |
| NeoASAS [14] | Active | - Force sensors | - Detection of user’s intentions | - Free | - | - |
| UFES [16,28] | Active | - Force sensors - LRF - IMUs - Encoders |
- Path following - Obstacle avoidance - Detection of user’s intentions - Gait monitoring |
- Free - Supervised - Feedback |
Spatially modulated admittance control, visual feedback |
- |
| PAMM [29] | Active | - Force sensors - Sonars - Camera - Encoders |
- Autonomous navigation - Health monitoring |
User control, path following control |
Adaptive and shared admittance controller |
- |
| MOBOT [17,30,31,32] |
Active | - Force sensors - LRFs - Cameras - Kinect sensors - Microphones |
- Autonomous navigation - Detection of user’s intentions - Speech and gesture recognition - Body pose estimation - Gait Analyzer |
Walking assitance, sit-to-stand assistance, nurse type |
Adaptive control based on context |
- |
| CAIROW [33] | Active | - Force sensors - LRFs |
- Environment analyzer - Force analyzer - Gait analyzer |
Context aware mode |
Adaptive system parameters |
- |
| ISR-AIWALKER [34,35] |
Active | - Force sensors - Kinect sensor -Encoders - Leap motion sensor - RGB-D Camera |
- Detection of user’s intention - Gripping recognition - Gait analyzer - Autonomous navigation |
- Supervised - Navigation aided |
Aided user intent by navigation system |
- |
| COOL Aide [36] | Passive | - Force sensors - LRF - Encoders |
- Autonomous navigation - Detection of user’s intentions |
- Supervised | Shared control based on obstacles and user’s intentions |
- |
| Wachaja et al. [37] |
Passive | - LRF - Tilting LRF |
- 3D Mapping and localization - Obstacle avoidance - Vibrotactile feedback |
- Single feedback - Multiple feedback |
- | - |
| MARC [38,39] | Passive | - Sonars - Infrared sensors - Encoders |
- Path following - Obstacle avoidance |
Warning mode, safety braking mode and braking and steering mode |
Shared walker steering |
- |
| c-Walker [40] | Passive | - Kinect like sensor - RFID reader - IMU - Camera - Encoders |
- Autonomous navigation - People detection and tracking - Guidance |
Acoustic feedback, mechanic feedback and haptic feedback |
Shared walker steering |
Social Force Model for path planning |