“The robot system and operator may move concurrently in the collaborative workspace. Risk reduction is achieved by maintaining at least the protective separation distance between operator and robot at all times. During robot motion, the robot system never gets closer to the operator than the protective separation distance. When the separation distance decreases to a value below the protective separation distance, the robot system stops.’’—ISO/TS 15066, 5.5.4.

In systems employing SSM, the robot workspace is divided into three zones:

The protective separation distance S_p is calculated using the following formula:

$S_p\left(t_0\right)=S_h+S_r+S_s+C+Z_d+Z_r$(1)

where:

The formula can be expressed in greater detail as:

$S_{p\left(t_0\right)}={\displaystyle {\int }_{t_0}^{t_0+T_r+T_s}{v}_h\left(t\right)\text{d}t+}{\displaystyle {\int }_{t_0}^{t_0+T}{v}_r\left(t\right)\text{d}t}+{\displaystyle {\int }_{t_0}^{t_0+T_r+T_s}{v}_s\left(t\right)\text{d}t}+C+Z_d+Z_r$ (2)

where:

If the real-time separation distance S falls below S_p, the robot will go into a safety stop or lower its speed, illustrated in Figure 5 .

Although Equation (2) provides dynamic calculation for S_p, real-time implementation poses challenges:

Measuring Human Speed

Current monitoring devices, such as lidar or vision-based systems, are typically limited to detecting intrusions into predefined safety zones. They don’t distinguish between humans and other (non)-hazards. While algorithms exist to detect and classify intrusions as human operators, their reliability is insufficient for safety-critical applications [20] . They often fail to ensure no operator is present in the workspace. Moreover, even when a sensing system successfully detects and locates a human operator, the tracking has to be accurate. Detection delay and latency in reporting can lead to inaccuracies in the calculated separation distance [21] [22] .

Signal Transmission

Another critical limitation is the ability to transmit measured data in compliance with safety standards. For SSM systems to meet standards such as Performance Level d¹, the communication of sensor data must be both fast and highly reliable. Currently, most sensing systems and their associated data transmission technologies are not safety-rated. For instance, real-time Ethernet-based communication between sensors and controllers, while capable of transmitting position and velocity data is not safety-rated.

Directed Speed

The concept of directed speed for both the robot and the operator can lead to confusion in calculating the separation distance. Consider a scenario where the robot and operator are moving toward each other at an angle θ, as illustrated in Figure 6 . In this case, the directed speed at any given instance is reduced by a factor of cos(θ) relative to their trajectory speeds. This reduction in directed speed results in a smaller separation distance, S_p, which can create unsafe conditions if not properly accounted for. The ISO/TS 15066 standard attempts to address such cases by stating: “The system shall be designed to account for v_h and v_r varying in the manner that reduces the separation distance S the most.” This implies that the trajectory speed must be used in calculations to ensure safety. However, this directive is open to interpretation, particularly in complex motion scenarios. For example, consider a robot moving parallel to an operator who remains stationary. As the robot approaches, its directed speed relative to the operator decreases. Intuitively, one might expect the safety zone to grow as the distance between the robot and operator decreases. However, there is no explicit guideline in the standard to handle such situations dynamically. The conclusion is that the standard lacks a clear, absolute rule for interpreting the speeds of the robot and operator. It only emphasizes the need to account for the worst-case scenario.

Current Situation

Therefore, in practice, static estimates are often used for protective distances, considering worst-case scenarios. Equations (3) and (4) can be used to estimate a constant value for respectively S_h and S_r if the operator and robot speed are not monitored.

$S_h=v_h\ast \left(T_r+T_s\right)$ (3)

$S_r=v_r\ast T_r$ (4)

Simplifying Equation (1) results in the minimum distance formula presented in ISO 13855 [23] . Equation (5) gives the minimum protection distance S_p for stationary machines:

$S_p=\left(K\ast T\right)+S_m+D_{DS}+Z$ (5)

where:

A recent revision of ISO 13855:2024 added a “dynamic’’ distance factor S_m to account for moving hazards, such as AGVs or industrial robots mounted on an external axis. The operator’s speed is typically assumed to be 1.6 m/s per ISO 13855. The robot’s speed is set to its maximum programmed or limited value. In the Safe Speed Zone, for example, the robot speed is often reduced to 250 mm/s, corresponding to the safety speed of the Tool Center Point (TCP) [24] .

Dynamic safety systems must overcome current technological limitations to measure operator and robot speeds reliably. Until then, in industrial settings, protective separation distances are calculated conservatively to ensure compliance with safety standards.

ISO/TS 15066 does not prescribe detailed methods for implementing SSM. Designers have the freedom to select the appropriate sensors, determine their configuration, and define the geometry of the safety zones. This section aims to categorize SSM techniques for clarity and adaptability, facilitating the incorporation of existing methods and potential future advancements.

SSM types can be divided based on the monitoring method and based on the separation distance calculations. This results in six different SSM possibilities: Fixed Sized, Variable Sized and Variable Shaped SSM with either Static or Mobile Monitoring Figure 7 gives an overview of the categories.

The monitoring method depends on the position of the defined safety zones relative to the environment. The zones can have a fixed center position, static monitoring, or moving center, mobile monitoring. Mobile monitoring can be used to secure an Automated Guided Vehicle (AGV) or Autonomous Mobile Robot (AMR). Mobile monitoring does not necessarily mean that the monitoring device is moving. It can also be a software adjustment where the safety zones are programmed to move with the robotic system. Another example of mobile monitoring in [25] , where the safety zone around every robot link move according to the joint position.

Depending on how the protective separation distance S_p is calculated, there is:

In literature, terms such as static, dynamic, and adaptive SSM are frequently used. While they align with the above categories, they can sometimes cause confusion. For example, a dynamic SSM may employ static monitoring, or a fixed sized zone may move with the robotic system, appearing dynamic. The zones may move but S_p isn’t necessarily dynamic. Therefore, the two proposed categories.

2D safety laser scanners are commonly used to define fixed safety zones. Devices from manufacturers such as SICK and PILZ offer safety performance levels up to PLd. These scanners can monitor both Safe Speed (yellow) and Safe Stop Zones (red), with some models supporting up to 8 independently configurable zones [26] [27] . Modern solutions like Safe Robotics Area Protection simplify integration with robot controllers, enabling straightforward implementation of speed reduction [28] .

3D safety sensors are emerging as an advanced alternative to traditional 2D scanners, providing a more comprehensive understanding of the workspace [29] [30] . This is clearly visible in Figure 9 . Examples include sensors using time-of-flight, radar, or vision-based technologies [31] [32] . While 3D systems are in their infancy, ongoing research and development promise significant improvements in reliability and safety compliance [33] [34] .

Advantages of 3D methods:

Disadvantages of 3D methods:

Mobile monitoring has advantages when the robot has a large workspace. Unlike static monitoring, mobile safety zones dynamically adjust their position to the robot’s position. Importantly, this concept does not necessarily require physically moving the sensors; instead, it can rely on software-controlled adjustments of the zone position.

Advantages of Mobile Monitoring:

Disadvantages of Mobile Monitoring:

Example:

Consider a six-axis industrial robot (TX2-90L, Stäubli) mounted upside down on a horizontal rail Figure 10 . The rail is positioned in front of a vertical storage warehouse (Logimat, SSI Schäfer), where the robot retrieves and stores goods. In the centre of the rail, a 2D safety scanner (nanoScan3, Sick) is mounted. Above the robot, a LIDAR + RGB camera (Titan S2, Neuvition), is mounted that moves with the rail.

S_p is calculated from Equation (6) [35] , which is derived from Equation (1) for constant robot and operator speed. Table 1 shows the calculated values. A comparison is made between a robot mounted on the floor. The reach of the robot is not added to the total distance as it remains the same in every situation.

$S_p=v_h\ast \left(T_r+T_s\right)+v_r\left(t_0\right)\ast T_r+B+C$(6)

Figure 11 shows that a too large safety zone must be set in the case of static monitoring. A red zone of 7348 mm long is required, as the position of the robot is not accounted for. Therefore, the red zone extends over the whole length of the external axis.

Conclusion:

Fixed Shaped SSM offers a straightforward approach to ensuring robotic safety but comes with limitations in static implementations, particularly for dynamic workspaces or mobile robots. Advances in sensor technology, especially 3D safety scanners and mobile safety zones, provide promising solutions to these challenges. By adopting these modern methods, systems can achieve higher safety levels while minimizing operational dead time and improving overall efficiency.